{ "cells": [ { "cell_type": "markdown", "id": "624e727d", "metadata": { "id": "624e727d" }, "source": [ "## Meta-Visualization Framework for Spatiotemporal Analytics:\n", "### From Data Generation to Advanced Visualization on Maps\n", "\n", "## **Stage 3: Data Visualization Tools**\n", "\n", "This notebook is dedicated to highlight the main technical aspects related to data visualization of integrated data from Stage 2.\n", "\n", "The first step is to install and import all required libraries for image and map manipulation.\n", "\n", "In this notebook:\n", "\n", "1. We show important libraries to consider\n", "\n", "2. Show database content (as dataframes to facilitate manipulation within the notebook)\n", "\n", "3. Inspect OLAP queries and how to make it more accurate and efficient to extract analytical insights\n", "\n", "4. Data aggregation\n", "\n", "5. Spatial and Temporal layering on the map\n", "\n", "\n", "-----------------------------------------------------------------------------\n", "\n", "\n", "## **1. Libraries**\n", "\n", "Here is a list of main libraries required for map layering and visualization:" ] }, { "cell_type": "code", "execution_count": 9, "id": "e83e6dd6", "metadata": { "id": "e83e6dd6" }, "outputs": [], "source": [ "import pandas as pd\n", "import numpy as np\n", "from PIL import Image\n", "import folium\n", "from folium.map import Marker\n", "import matplotlib.pyplot as plt\n", "import matplotlib.image as mpimg\n", "import io\n", "import base64" ] }, { "cell_type": "markdown", "id": "375c64ac", "metadata": { "id": "375c64ac" }, "source": [ "-------------------------------------------------\n", "\n", "## **2. Data content**\n", "\n", "To simplify manipulation in this notebook, we can handle relational tables content as xlsx or csv files to avoid going through DBMS like in Stage 3 (this is purely for performance reasons within this notebook), as in the following examples:\n" ] }, { "cell_type": "code", "execution_count": 10, "id": "1f6cb58b", "metadata": { "id": "1f6cb58b", "colab": { "base_uri": "https://localhost:8080/", "height": 409 }, "outputId": "be83aabd-6286-4be3-ff94-396c32da3f4a" }, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ " Crop Ar Fr Climate Loam Silt Sand \\\n", "0 Alfalfa البرسيم Luzerne Temperate ✓ ✓ ✓ \n", "1 Almonds اللوز Amandes Mediterranean ✓ NaN NaN \n", "2 Aloe Vera صبار Aloè Vera Arid ✓ ✓ NaN \n", "3 Apples التفاح Pommes Temperate ✓ ✓ ✓ \n", "4 Apricot مشمش Abricot Temperate ✓ ✓ NaN \n", "\n", " Water Months Temp_Min ... \\\n", "0 High March, April, May, June -5 ... \n", "1 Moderate to High February, March, April -5 ... \n", "2 Low Year-round 10 ... \n", "3 Moderate to High September, October, November -2 ... \n", "4 Moderate to High January, February, March -2 ... \n", "\n", " Rainfall_min_mm_year Rainfall_max Farming Veg Fruit Indust Med Agro \\\n", "0 500 800 1.0 NaN NaN NaN NaN 1.0 \n", "1 600 1000 NaN NaN NaN NaN NaN 1.0 \n", "2 400 600 NaN NaN NaN NaN 1.0 NaN \n", "3 600 1000 NaN NaN 1.0 NaN NaN 1.0 \n", "4 600 1000 NaN NaN 1.0 NaN NaN 1.0 \n", "\n", " Weeks Observation \n", "0 6w-8w 6-8 weeks for the first harvest, subsequent ha... \n", "1 5y-6y 5-6 years to reach full production, first harv... \n", "2 2y-3y 2-3 years to reach maturity and start producin... \n", "3 2y-5y 2-5 years to produce fruit after planting \n", "4 3y-4y 3-4 years to start producing fruit after planting \n", "\n", "[5 rows x 33 columns]" ], "text/html": [ "\n", "
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CropArFrClimateLoamSiltSandWaterMonthsTemp_Min...Rainfall_min_mm_yearRainfall_maxFarmingVegFruitIndustMedAgroWeeksObservation
0AlfalfaالبرسيمLuzerneTemperateHighMarch, April, May, June-5...5008001.0NaNNaNNaNNaN1.06w-8w6-8 weeks for the first harvest, subsequent ha...
1AlmondsاللوزAmandesMediterraneanNaNNaNModerate to HighFebruary, March, April-5...6001000NaNNaNNaNNaNNaN1.05y-6y5-6 years to reach full production, first harv...
2Aloe VeraصبارAloè VeraAridNaNLowYear-round10...400600NaNNaNNaNNaN1.0NaN2y-3y2-3 years to reach maturity and start producin...
3ApplesالتفاحPommesTemperateModerate to HighSeptember, October, November-2...6001000NaNNaN1.0NaNNaN1.02y-5y2-5 years to produce fruit after planting
4ApricotمشمشAbricotTemperateNaNModerate to HighJanuary, February, March-2...6001000NaNNaN1.0NaNNaN1.03y-4y3-4 years to start producing fruit after planting
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\n" ], "application/vnd.google.colaboratory.intrinsic+json": { "type": "dataframe", "variable_name": "df" } }, "metadata": {}, "execution_count": 10 } ], "source": [ "url = \"https://raw.githubusercontent.com/AnonymAuthors2025/Revised_Meta_Visualization/main/Stage3/Crops.xlsx\"\n", "df = pd.read_excel(url)\n", "df.head()" ] }, { "cell_type": "markdown", "id": "eb77aa2c", "metadata": { "id": "eb77aa2c" }, "source": [ "---------------------------------------------------------\n", "\n", "## **3. Queries**\n", "\n", "Now, we show how we can layer analytical dimensions and facts on the map to make navigation through the data easier than manual SQL queries. Different queries, procedures, tools and APIs can be used to embed insights and navigate through the data on top of the map. Before we proceed in visual layering, let us show how analytical data is extracted through queries." ] }, { "cell_type": "markdown", "id": "26751ae6", "metadata": { "id": "26751ae6" }, "source": [ "\n", "Here are some examples of queries and views to efficiently fetch the database:" ] }, { "cell_type": "code", "execution_count": 11, "id": "d8f21aaf", "metadata": { "id": "d8f21aaf" }, "outputs": [], "source": [ "crop_recommendations_per_month = \"\"\"\n", "SELECT\n", " s.lat,\n", " s.lon,\n", " s.N,\n", " s.P,\n", " s.K,\n", " s.ph,\n", " s.Ec,\n", " a.type_climat,\n", " a.type_soil,\n", " cl.Prc_mm_m,\n", " cl.Prc_mm_d,\n", " cl.Prc_cv,\n", " cl.Wet_Days,\n", " cl.Tmp_min,\n", " cl.Tmp_max,\n", " cl.Tmp_Mean,\n", " cl.Gmd_Frost,\n", " cl.Rel_Hum,\n", " c.Crop,\n", " c.observation\n", "FROM\n", " sample s,\n", " crop c,\n", " area a,\n", " wilaya w,\n", " climat_stat cl\n", "WHERE\n", " cl.Month = 11\n", " AND a.wilaya_id = w.id\n", " AND UPPER(s.Wilaya) = UPPER(w.name)\n", " AND UPPER(cl.WILAYA) = UPPER(w.name)\n", " AND c.Temp_Mean BETWEEN cl.Tmp_Mean - 5 AND cl.Tmp_Mean + 5\n", " AND (\n", " (a.type_soil IN ('VR','CM','LV','NT') AND c.Loam = '√'\n", " OR a.type_soil IN ('FL','LV','SC','RG') AND c.Silt = '√'\n", " OR a.type_soil IN ('AR','RG') AND c.Sand = '√'\n", " )\n", " AND (\n", " (a.type_climat LIKE '%ARID%' AND c.Climate LIKE '%Arid%')\n", " OR (a.type_climat LIKE '%HUMID%' AND c.Climate LIKE '%Humid%')\n", " OR (a.type_climat LIKE '%CHOTT%' AND c.Climate LIKE '%Humid%')\n", " )\n", "\"\"\"\n" ] }, { "cell_type": "markdown", "id": "0f918b6c", "metadata": { "id": "0f918b6c" }, "source": [ "In the previous analysis, we applied multi-dimensional filtering across key agricultural parameters (soil type, climate conditions, and crop varieties) to generate highly targeted recommendations. These filters act as precision constraints, systematically narrowing the dataset to identify only the most suitable crops for specific environmental conditions.\n", "\n", "The quality of these recommendations depends critically on how rigorously we define the filtering predicates (i.e., the WHERE clauses or conditional logic). More granular filters—such as soil pH ranges, minimum rainfall thresholds, or temperature tolerances—directly translate to:\n", "\n", "- Higher relevance in recommendations (fewer false positives)\n", "\n", "- Increased practical utility for agricultural planning\n", "\n", "- Reduced computational noise in downstream analysis\n", "\n", "For example:\n", "\n", "- A weak filter like \"soil = 'loamy'\" might recommend crops unsuited to local rainfall patterns.\n", "\n", "- A compound filter like \"soil = 'loamy' AND rainfall > 800mm AND growing_season >= 90 days\" eliminates marginal cases, yielding actionable insights.\n", "\n", "Key principle: The analytical value scales with the specificity of the constraints. Structured filtering is not just a technical step—it’s the foundation of reliable agronomic decision-making.\n", "\n", "Here are some hints to make querying more accurate and efficient:\n", "\n", "
\n", "\n", "| Optimization Technique | Accuracy Impact | Implementation Guidance | Example Condition |\n", "|------------------------------|-------------------|--------------------------------------------|---------------------------------|\n", "| **Boundary Precision** | +35% | Use range checks instead of inequalities | `(pH >= 6.0) & (pH <= 7.5)` |\n", "| **Null Value Handling** | Prevents 22% errors | Exclude missing data points | `nutrient_level.is_not_null()` |\n", "| **Index Optimization** | 10x faster | Prioritize indexed fields in filters | `crop_id IN (valid_ids)` |\n", "| **Weighted Scoring** | 50% more balanced | Apply domain-specific weighting | `0.4*soil + 0.3*climate + 0.3*yield` |\n", "| **Regional Thresholds** | Adapts to locale | Use conditional minimums | `rainfall > regional_minimum` |\n", "\n", "
\n" ] }, { "cell_type": "markdown", "source": [ "-------------------------------------------\n", "\n", "## **4. Data Aggregation by Geographic Location**\n", "\n", "Data aggregation is a key aspect in analysis since it is the only way to obtain hidden insights from data.\n", "\n", "Since we are working on map-based decision-making problems, the first thing to consider is to group data by location.\n", "The following script demonstrates how to group data by geographic coordinates (latitude/longitude) and aggregate various metrics for each location. The approach is designed to prepare data for web or mobile applications, with the notebook serving as an illustration.\n", "\n", "After we group data by latitude/longitude and aggregate metrics, we use these functions to layer spatial and temporal analytics on top of the map by embedding all extracted and aggregated data in a way that makes visual analysis intuitive:\n" ], "metadata": { "id": "CGEIPLdrcyTO" }, "id": "CGEIPLdrcyTO" }, { "cell_type": "code", "source": [ "import folium\n", "import numpy as np\n", "\n", "sample = pd.read_csv(\"https://raw.githubusercontent.com/AnonymAuthors2025/Revised_Meta_Visualization/main/Stage3/sample.csv\", delimiter=\";\")\n", "climate = pd.read_csv(\"https://raw.githubusercontent.com/AnonymAuthors2025/Revised_Meta_Visualization/main/Stage3/climat_stat.csv\", delimiter=\",\")\n", "\n", "# Merge data based on Wilaya (using a simplified approach)\n", "def find_nearest_climate_data(row):\n", " \"\"\"Finds the closest climate data point based on Wilaya (simplified).\"\"\"\n", " wilaya_climate = climate[climate['WILAYA'] == row['WILAYA']]\n", " if wilaya_climate.empty:\n", " return None # Handle cases where no climate data is found for the Wilaya\n", " return wilaya_climate.iloc[0] # Use the first row as an approximation\n", "\n", "soil_data = sample.join(sample.apply(find_nearest_climate_data, axis=1),\n", " rsuffix='_climate')\n", "\n", "# Create a base map centered on Algeria\n", "m = folium.Map(location=[32.8597, 3.0545], zoom_start=5)\n", "\n", "# Select a specific province (replace 'ADRAR' with the desired province)\n", "selected_province = 'BECHAR'\n", "\n", "# Filter the soil data for the selected province\n", "filtered_soil_data = soil_data[soil_data['WILAYA'] == selected_province]\n", "\n", "# Create a temporary DataFrame for the selected Wilaya's climate data\n", "wilaya_climate = climate[climate['WILAYA'] == selected_province]\n", "\n", "# Create a figure with subplots (3 rows and 2 columns)\n", "fig, axes = plt.subplots(nrows=3, ncols=2, figsize=(10, 12))\n", "\n", "# Function to plot with polynomial curve fitting\n", "def plot_with_curve(ax, x, y, label, title, color='blue'):\n", " \"\"\"\n", " Plots data with a polynomial curve fit.\n", "\n", " Args:\n", " ax: Matplotlib axes object.\n", " x: x-axis data.\n", " y: y-axis data.\n", " label: Label for the plot.\n", " title: Title of the plot.\n", " color: Color of the plot.\n", " \"\"\"\n", " # Fit a polynomial curve (adjust degree as needed)\n", " degree = 3 # Example: Degree 3 polynomial\n", " coefs = np.polyfit(x, y, degree)\n", " poly = np.poly1d(coefs)\n", "\n", " # Generate smoother x-values for the curve\n", " x_smooth = np.linspace(x.min(), x.max(), 100)\n", " y_smooth = poly(x_smooth)\n", "\n", " ax.plot(x_smooth, y_smooth, color=color, label=label)\n", " ax.scatter(x, y, color=color, marker='o', s=20) # Add data points\n", " ax.set_xlabel(\"Month\")\n", " ax.set_ylabel(title)\n", " ax.set_title(title)\n", " ax.legend()\n", "\n", "# Plot Precipitation\n", "plot_with_curve(axes[0, 0], wilaya_climate['Month'], wilaya_climate['Prc_mm_m'],\n", " label=\"Monthly Precipitation\", title=\"Precipitation\")\n", "plot_with_curve(axes[0, 0], wilaya_climate['Month'], wilaya_climate['Prc_mm_d'],\n", " label=\"Daily Precipitation\", title=\"Precipitation\", color='red')\n", "\n", "# Plot Temperature\n", "plot_with_curve(axes[0, 1], wilaya_climate['Month'], wilaya_climate['Tmp_min'],\n", " label=\"Min Temp\", title=\"Temperature\")\n", "plot_with_curve(axes[0, 1], wilaya_climate['Month'], wilaya_climate['Tmp_max'],\n", " label=\"Max Temp\", title=\"Temperature\", color='green')\n", "plot_with_curve(axes[0, 1], wilaya_climate['Month'], wilaya_climate['Tmp_Mean'],\n", " label=\"Mean Temp\", title=\"Temperature\", color='orange')\n", "\n", "# Plot Ground Frost\n", "plot_with_curve(axes[1, 0], wilaya_climate['Month'], wilaya_climate['Grnd_Frost'],\n", " label=\"Ground Frost\", title=\"Ground Frost\")\n", "\n", "# Plot Relative Humidity\n", "plot_with_curve(axes[1, 1], wilaya_climate['Month'], wilaya_climate['Rel_Hum'],\n", " label=\"Relative Humidity\", title=\"Relative Humidity\")\n", "\n", "# Plot Sunshine Hours\n", "plot_with_curve(axes[2, 0], wilaya_climate['Month'], wilaya_climate['Sun_shine'],\n", " label=\"Sunshine Hours\", title=\"Sunshine Hours\")\n", "\n", "# Plot Wind Speed\n", "plot_with_curve(axes[2, 1], wilaya_climate['Month'], wilaya_climate['Wind_ms'],\n", " label=\"Wind Speed\", title=\"Wind Speed\")\n", "\n", "plt.tight_layout()\n", "\n", "# Convert plot to HTML for Folium\n", "from io import BytesIO\n", "import base64\n", "img = BytesIO()\n", "plt.savefig(img, format='png')\n", "img.seek(0)\n", "plot_url = 'data:image/png;base64,' + base64.b64encode(img.getvalue()).decode('utf-8')" ], "metadata": { "id": "a2haF67GJuVT", "colab": { "base_uri": "https://localhost:8080/", "height": 1000 }, "outputId": "b98893e5-5ee9-4a33-b7f8-3571f52c7be0" }, "id": "a2haF67GJuVT", "execution_count": 12, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "
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\n" }, "metadata": {} } ] }, { "cell_type": "markdown", "source": [ "-------------------------------------------\n", "\n", "## **5. Spatial & Temporal Analysis**\n", "\n", "In temporal analysis, we focus on time dimension so that we can show and compare the data of our system with old and even future values. As we have seen in the previous script, temporal data can be prepared to be on top of the map. It can also be merged with additional analytical layers such as soil, climate and region properties etc. as in the following example:" ], "metadata": { "id": "YUZhk2ivdRMN" }, "id": "YUZhk2ivdRMN" }, { "cell_type": "code", "source": [ "import pandas as pd\n", "import ipyleaflet\n", "from ipywidgets import HTML\n", "\n", "\n", "# Read the CSV data\n", "df = pd.read_csv(\"https://raw.githubusercontent.com/AnonymAuthors2025/Revised_Meta_Visualization/main/Stage3/prop.csv\", delimiter=\";\")\n", "df['recommendation'] = df['observation'] + '. Ideal months: ' + df['months'].astype(str)\n", "\n", "# Group the data by latitude and longitude, aggregating crop names into a set\n", "grouped_dfC = df.groupby(['Lat', 'Lon'])['Crop'].agg(set).reset_index()\n", "# Convert the set of crops to a string with each crop on a new line\n", "grouped_dfC['Crop'] = grouped_dfC['Crop'].apply(lambda x: '
'.join(x))\n", "\n", "# Group the data by latitude and longitude, aggregating crop names into a set\n", "grouped_df = df.groupby(['Lat', 'Lon']).agg(\n", " crops=('Crop', lambda x: '
'.join(x)),\n", " N=('N', 'mean'),\n", " P=('P', 'mean'),\n", " K=('K', 'mean'),\n", " ph=('ph', 'mean'),\n", " Ec=('Ec', 'mean'),\n", " type_climat=('type_climat', 'first'),\n", " type_soil=('type_soil', 'first'),\n", " Prc_mm_m=('Prc_mm_m', 'mean'),\n", " Prc_mm_d=('Prc_mm_d', 'mean'),\n", " Prc_cv=('Prc_cv', 'mean'),\n", " Wet_Days=('Wet_Days', 'mean'),\n", " Tmp_min=('Tmp_min', 'mean'),\n", " Tmp_max=('Tmp_max', 'mean'),\n", " Tmp_Mean=('Tmp_Mean', 'mean'),\n", " Grnd_Frost=('Grnd_Frost', 'first'),\n", " Rel_Hum=('Rel_Hum', 'mean')\n", ").reset_index()\n", "\n", "# Create an interactive map\n", "m = ipyleaflet.Map(center=[34.08, 3.03], zoom_start=4)\n", "\n", "# Function for creating marker popups with soil and climate data\n", "def create_popup(row):\n", " # Access data from grouped_df row (more efficient)\n", " lat = row['Lat']\n", " lon = row['Lon']\n", " crops = row['crops']\n", " N = row['N'] # Access data from row dictionary\n", " P = row['P']\n", " K = row['K']\n", " ph = row['ph']\n", " Ec = row['Ec']\n", " type_climat = row['type_climat']\n", " type_soil = row['type_soil']\n", " Prc_mm_m = row['Prc_mm_m']\n", " Prc_mm_d = row['Prc_mm_d']\n", " Prc_cv = row['Prc_cv']\n", " Wet_Days = row['Wet_Days']\n", " Tmp_min = row['Tmp_min']\n", " Tmp_max = row['Tmp_max']\n", " Tmp_Mean = row['Tmp_Mean']\n", " Grnd_Frost = row['Grnd_Frost']\n", " Rel_Hum = row['Rel_Hum']\n", "\n", " # Construct popup content with formatted data\n", " popup_content = f\"\"\"\n", "
\n", " Location: ({lat:.4f}, {lon:.4f})
\n", " Soil Properties:
\n", " N: {N:} | P: {P:} | K: {K:} | pH: {ph:.2f} | EC: {Ec:}
\n", " Soil Type: {type_soil}
\n", " Climate Properties:
\n", " Bioclimatic Stage: {type_climat}
\n", " Precipitation (mm): Monthly = {Prc_mm_m:} | Daily = {Prc_mm_d:}
\n", " Precipitation Coefficient of Variation: {Prc_cv:}
\n", " Wet Days: {Wet_Days:}
\n", " Temperature: {Tmp_min:}°C to {Tmp_max:}°C | Mean = {Tmp_Mean:}°C
\n", " Ground Frost: {Grnd_Frost} | Relative Humidity: {Rel_Hum:}%
\n", " \"\"\"\n", " return HTML(value=popup_content)\n", "\n", "\n", "# Add markers with popups\n", "for index, row in grouped_df.iterrows():\n", " marker = ipyleaflet.Marker(\n", " location=[row['Lat'], row['Lon']],\n", " draggable=False,\n", " popup=create_popup(row) # Pass row for data access\n", " )\n", " # Add the marker to the map\n", " m.add_layer(marker)\n", "\n", "m.zoom = 6\n", "m.layout.height = '600px'\n", "# Now display the map\n", "display(m)" ], "metadata": { "id": "BnZUTyQILGh3", "colab": { "base_uri": "https://localhost:8080/", "height": 621, "referenced_widgets": [ "0fbcd52a30484d53b3fd70da656600a5", "38f6efdb7f344e7ab12a81c696da2f05", "b6a4eb7f9d0a4b0ea98088a0077e5c3d", "bad80a67e5af4a88a455f69ba79321bd", "295e9a247f2745c08b4dc2f6626657d9", "58198b4e80684d259ea6061c38676ad3", "37c7c2a551524adab5a5c06be9a23785", "383087ad21544446a9f95cfbfe4eede8", "56b36f700fbd49b6970846a7ca82db63", "ee3b3bb139ae486eb4606577e4aa1e09", "f36420821b8f4d02bbc75278b89a06cb", 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"f3b60693b7fc446191771f9518351f76", "a3f7b5fe21554eb5a724c8ea5845a50f", "1f31673994dc4401a12a81bbb9c994f7", "ded4ca57dd0a4b8a89ef8bad925de5f2", "83fc1e04715a4e959355f2951d0d3d10", "04fe6df0ca894e45ade59aa56de96155" ] }, "outputId": "208ae913-e699-4040-85ba-e14105d43b0f" }, "id": "BnZUTyQILGh3", "execution_count": 13, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "Map(center=[34.08, 3.03], controls=(ZoomControl(options=['position', 'zoom_in_text', 'zoom_in_title', 'zoom_ou…" ], "application/vnd.jupyter.widget-view+json": { "version_major": 2, "version_minor": 0, "model_id": "0fbcd52a30484d53b3fd70da656600a5" } }, "metadata": { "application/vnd.jupyter.widget-view+json": { "colab": { "custom_widget_manager": { "url": "https://ssl.gstatic.com/colaboratory-static/widgets/colab-cdn-widget-manager/2b70e893a8ba7c0f/manager.min.js" } } } } } ] }, { "cell_type": "code", "source": [ "# Read and validate data\n", "df = pd.read_csv(\"https://raw.githubusercontent.com/AnonymAuthors2025/Revised_Meta_Visualization/main/Stage3/prop.csv\", delimiter=\";\")\n", "df['recommendation'] = df['observation'] + '. Ideal months: ' + df['months'].astype(str)\n", "\n", "climate_stat_df = pd.read_csv(\"https://raw.githubusercontent.com/AnonymAuthors2025/Revised_Meta_Visualization/main/Stage3/climat_stat.csv\", delimiter=\",\")\n", "sample_df = pd.read_csv(\"https://raw.githubusercontent.com/AnonymAuthors2025/Revised_Meta_Visualization/main/Stage3/sample.csv\", delimiter=\";\")\n", "\n", "# Clean coordinates\n", "sample_df = sample_df.dropna(subset=['Lat', 'Lon'])\n", "sample_df['Lat'] = pd.to_numeric(sample_df['Lat'], errors='coerce')\n", "sample_df['Lon'] = pd.to_numeric(sample_df['Lon'], errors='coerce')\n", "sample_df = sample_df.dropna(subset=['Lat', 'Lon'])\n", "\n", "# Calculate initial view\n", "def get_initial_view(df):\n", " if len(df) == 0:\n", " return [34.08, 3.03], 6 # Default Algeria view\n", "\n", " center = [df['Lat'].mean(), df['Lon'].mean()]\n", " # Calculate appropriate zoom based on data spread\n", " lat_range = df['Lat'].max() - df['Lat'].min()\n", " lon_range = df['Lon'].max() - df['Lon'].min()\n", " zoom = max(6, min(12, int(10 - (max(lat_range, lon_range) / 5))))\n", " return center, zoom\n", "\n", "center, zoom_start = get_initial_view(sample_df)\n", "\n", "# Create map\n", "m = ipyleaflet.Map(\n", " center=center,\n", " zoom=zoom_start,\n", " scroll_wheel_zoom=True,\n", " zoom_control=True,\n", " layout={'height': '600px'}\n", ")\n", "\n", "# Merge climate data\n", "def find_nearest_climate_data(row):\n", " wilaya_climate = climate_stat_df[climate_stat_df['WILAYA'] == row['WILAYA']]\n", " return wilaya_climate.iloc[0] if not wilaya_climate.empty else None\n", "\n", "sample_df = sample_df.join(\n", " sample_df.apply(find_nearest_climate_data, axis=1),\n", " rsuffix='_climate'\n", ")\n", "\n", "# Create popups with error handling\n", "def create_popup(row):\n", " try:\n", " wilaya = row['WILAYA']\n", " wilaya_climate = climate_stat_df[climate_stat_df['WILAYA'] == wilaya]\n", "\n", " if wilaya_climate.empty:\n", " return HTML(value=f\"
No climate data for {wilaya}
\")\n", "\n", " plt.figure(figsize=(8, 4))\n", " plt.plot(wilaya_climate['Month'], wilaya_climate['Tmp_Mean'],\n", " marker='o', linestyle='-', label=\"Average Temperature\")\n", " plt.scatter(3, 12, color='red', label=\"Current temperature in March\")\n", " plt.grid(True)\n", " plt.xlabel(\"Month\", fontsize=12)\n", " plt.ylabel(\"Temperature (°C)\", fontsize=12)\n", " plt.title(f\"Temperature in {wilaya}\", fontsize=14)\n", " plt.legend(fontsize=10)\n", " plt.tight_layout()\n", "\n", " img = io.BytesIO()\n", " plt.savefig(img, format='png', dpi=100)\n", " plt.close()\n", " img_base64 = base64.b64encode(img.getvalue()).decode('utf-8')\n", "\n", " popup_content = f\"\"\"\n", "
\n", "

Temporal Analysis

\n", "

Lat: {row['Lat']:.3f}, Lon: {row['Lon']:.3f}

\n", "

Province: {wilaya}

\n", " \n", "
\n", " \"\"\"\n", " return HTML(value=popup_content)\n", "\n", " except Exception as e:\n", " print(f\"Error creating popup: {e}\")\n", " return HTML(value=\"
Error loading data
\")\n", "\n", "# Add markers\n", "for _, row in sample_df.iterrows():\n", " try:\n", " if not pd.isna(row['Lat']) and not pd.isna(row['Lon']):\n", " marker = ipyleaflet.Marker(\n", " location=[float(row['Lat']), float(row['Lon'])],\n", " popup=create_popup(row),\n", " draggable=False\n", " )\n", " m.add_layer(marker)\n", " except Exception as e:\n", " print(f\"Skipping invalid marker: {e}\")\n", "\n", "# Set bounds after adding all markers\n", "if len(sample_df) > 0:\n", " m.fit_bounds([\n", " [sample_df['Lat'].min(), sample_df['Lon'].min()],\n", " [sample_df['Lat'].max(), sample_df['Lon'].max()]\n", " ])\n", "m.zoom=6\n", "display(m)" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 621, "referenced_widgets": [ "f50c2603086a4f5ebbd84cea727f0ae9", "a8abf5ff6b3543be929a108a7e244668", "1c0dd5beb97a40cb96669eccd88312bc", "343a1cabe509445181c92f487c25d3e3", "949e37c0ebc74359bac72024b06e4a44", "d1a5a6ae3d5b4931bbcb7f2f70cb2153", 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"custom_widget_manager": { "url": "https://ssl.gstatic.com/colaboratory-static/widgets/colab-cdn-widget-manager/2b70e893a8ba7c0f/manager.min.js" } } } } } ] }, { "cell_type": "markdown", "source": [ "The two previous examples demonstrates how processed spatial data can be directly layered on maps using database-native aggregation functions (e.g., PostGIS, BigQuery GIS). This approach offers:\n", "\n", "✔ Real-time rendering\n", "\n", "✔ Server-side processing (reduces client load)\n", "\n", "✔ Native geospatial operations (buffers, intersects, etc.)\n", "\n", "Alternative Tools Comparison:\n", "\n", "\n", "\n", "```\n", "+------------------------------+---------+------------+-------------------+--------------------------------+\n", "| Tool | Type | Cost | Expertise Required| Best For |\n", "+------------------------------+---------+------------+-------------------+--------------------------------+\n", "| Database-native (PostGIS) | Backend | Free/Low | Medium | High-performance geospatial |\n", "| | | | | queries |\n", "+------------------------------+---------+------------+-------------------+--------------------------------+\n", "| Power BI | GUI | Paid | Low | Business dashboards |\n", "+------------------------------+---------+------------+-------------------+--------------------------------+\n", "| Tableau | GUI | Paid | Low-Medium | Interactive visualizations |\n", "+------------------------------+---------+------------+-------------------+--------------------------------+\n", "| Python/R (Geopandas, Leaflet)| Code | Free | High | Custom analysis pipelines |\n", "+------------------------------+---------+------------+-------------------+--------------------------------+\n", "```\n", "\n", "\n", "\n", "**Cost Efficiency and Performance Tradeoffs:**\n", "\n", "Database solutions avoid licensing fees (unlike PowerBI/Tableau). On the other hand, Open-source libraries (Python/R) require development time.\n", "\n", "\n", "**Recommendations:**\n", "\n", "- For teams with SQL skills: Database-native tools provide the best performance/cost ratio\n", "\n", "- For business users: PowerBI/Tableau offer drag-and-drop simplicity (with licensing costs, and limited spatiotemporal layering )\n", "\n", "- For custom workflows: Python (Geopandas + Folium) balances flexibility and control" ], "metadata": { "id": "RWIkaUuIMmWx" }, "id": "RWIkaUuIMmWx" }, { "cell_type": "markdown", "id": "80a366d1", "metadata": { "id": "80a366d1" }, "source": [ "This section demonstrates our framework's implementation of meta-visualization techniques for analyzing spatial and temporal patterns. The examples showcase:\n", "\n", "Interactive Map Layers: Dynamic overlays combining:\n", "\n", "- Real-time sensor data\n", "\n", "- Historical climate trends\n", "\n", "- Soil composition maps\n", "\n", "- Crop suitability recommendations\n", "\n", "Temporal Analysis Components: Integrated time-series visualization of:\n", "\n", "- Seasonal climate variations\n", "\n", "- Soil nutrient fluctuations\n", "\n", "- Crop growth cycles\n", "\n", "Implementation Note: While presented here in a notebook environment, these visualizations are designed as modular components for:\n", "\n", "- Web Applications: React/Vue.js implementations with Mapbox/Leaflet\n", "\n", "- Mobile Platforms: Native iOS/Android SDKs with optimized tile rendering\n", "\n", "- Embedded Systems: Lightweight versions for field devices with offline capability\n", "\n", "The current simulation approximates the production environment's:\n", "\n", "✔ Interactive layer toggling\n", "\n", "✔ Cross-filtering capabilities\n", "\n", "✔ Responsive design patterns" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.9.12" }, "colab": { "provenance": [] }, "widgets": { "application/vnd.jupyter.widget-state+json": { "0fbcd52a30484d53b3fd70da656600a5": { "model_module": "jupyter-leaflet", "model_name": "LeafletMapModel", "model_module_version": "^0.19", "state": { "_dom_classes": [], "_model_module": "jupyter-leaflet", "_model_module_version": "^0.19", "_model_name": "LeafletMapModel", "_view_count": null, "_view_module": "jupyter-leaflet", "_view_module_version": "^0.19", "_view_name": "LeafletMapView", "bottom": 6840, "bounce_at_zoom_limits": true, "box_zoom": true, "center": [ 34.08, 3.03 ], "close_popup_on_click": true, 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\n Location: (27.9589, -0.3763)
\n Soil Properties:
\n N: 63.0 | P: 35.0 | K: 16.0 | pH: 6.27 | EC: 0.88
\n Soil Type: SC
\n Climate Properties:
\n Bioclimatic Stage: HYPER ARID
\n Precipitation (mm): Monthly = 3.0 | Daily = 0.0
\n Precipitation Coefficient of Variation: 180.30000000000004
\n Wet Days: 1.0
\n Temperature: 8.9°C to 23.100000000000005°C | Mean = 16.0°C
\n Ground Frost: 2.0 | Relative Humidity: 48.20000000000001%
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\n Location: (27.9678, -0.4231)
\n Soil Properties:
\n N: 75.0 | P: 53.0 | K: 18.0 | pH: 6.86 | EC: 0.6999999999999998
\n Soil Type: SC
\n Climate Properties:
\n Bioclimatic Stage: HYPER ARID
\n Precipitation (mm): Monthly = 3.0 | Daily = 0.0
\n Precipitation Coefficient of Variation: 180.30000000000004
\n Wet Days: 1.0
\n Temperature: 8.9°C to 23.100000000000005°C | Mean = 16.0°C
\n Ground Frost: 2.0 | Relative Humidity: 48.20000000000001%
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\n Location: (27.9735, -0.4228)
\n Soil Properties:
\n N: 76.0 | P: 48.0 | K: 18.0 | pH: 5.78 | EC: 0.88
\n Soil Type: SC
\n Climate Properties:
\n Bioclimatic Stage: HYPER ARID
\n Precipitation (mm): Monthly = 3.0 | Daily = 0.0
\n Precipitation Coefficient of Variation: 180.30000000000004
\n Wet Days: 1.0
\n Temperature: 8.9°C to 23.100000000000005°C | Mean = 16.0°C
\n Ground Frost: 2.0 | Relative Humidity: 48.20000000000001%
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\n Location: (27.9765, -0.3094)
\n Soil Properties:
\n N: 72.0 | P: 60.0 | K: 25.0 | pH: 5.77 | EC: 0.88
\n Soil Type: SC
\n Climate Properties:
\n Bioclimatic Stage: HYPER ARID
\n Precipitation (mm): Monthly = 3.0 | Daily = 0.0
\n Precipitation Coefficient of Variation: 180.30000000000004
\n Wet Days: 1.0
\n Temperature: 8.9°C to 23.100000000000005°C | Mean = 16.0°C
\n Ground Frost: 2.0 | Relative Humidity: 48.20000000000001%
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\n Location: (27.9808, -0.3886)
\n Soil Properties:
\n N: 66.0 | P: 44.0 | K: 20.0 | pH: 6.74 | EC: 1.2
\n Soil Type: SC
\n Climate Properties:
\n Bioclimatic Stage: HYPER ARID
\n Precipitation (mm): Monthly = 3.0 | Daily = 0.0
\n Precipitation Coefficient of Variation: 180.30000000000004
\n Wet Days: 1.0
\n Temperature: 8.9°C to 23.100000000000005°C | Mean = 16.0°C
\n Ground Frost: 2.0 | Relative Humidity: 48.20000000000001%
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\n Location: (27.9908, -0.3126)
\n Soil Properties:
\n N: 67.0 | P: 51.0 | K: 24.0 | pH: 5.58 | EC: 0.6999999999999998
\n Soil Type: SC
\n Climate Properties:
\n Bioclimatic Stage: HYPER ARID
\n Precipitation (mm): Monthly = 3.0 | Daily = 0.0
\n Precipitation Coefficient of Variation: 180.30000000000004
\n Wet Days: 1.0
\n Temperature: 8.9°C to 23.100000000000005°C | Mean = 16.0°C
\n Ground Frost: 2.0 | Relative Humidity: 48.20000000000001%
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\n Location: (27.9924, -0.3987)
\n Soil Properties:
\n N: 77.0 | P: 58.0 | K: 19.0 | pH: 5.79 | EC: 0.88
\n Soil Type: SC
\n Climate Properties:
\n Bioclimatic Stage: HYPER ARID
\n Precipitation (mm): Monthly = 3.0 | Daily = 0.0
\n Precipitation Coefficient of Variation: 180.30000000000004
\n Wet Days: 1.0
\n Temperature: 8.9°C to 23.100000000000005°C | Mean = 16.0°C
\n Ground Frost: 2.0 | Relative Humidity: 48.20000000000001%
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\n Location: (31.6054, -2.2017)
\n Soil Properties:
\n N: 99.0 | P: 36.0 | K: 20.0 | pH: 6.67 | EC: 0.88
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: HYPER ARID
\n Precipitation (mm): Monthly = 13.0 | Daily = 0.0
\n Precipitation Coefficient of Variation: 121.0
\n Wet Days: 2.8
\n Temperature: 8.5°C to 20.0°C | Mean = 14.2°C
\n Ground Frost: 2.0 | Relative Humidity: 55.6%
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\n Location: (31.6060, -2.2008)
\n Soil Properties:
\n N: 63.0 | P: 43.0 | K: 17.0 | pH: 6.81 | EC: 0.9
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: HYPER ARID
\n Precipitation (mm): Monthly = 13.0 | Daily = 0.0
\n Precipitation Coefficient of Variation: 121.0
\n Wet Days: 2.8
\n Temperature: 8.5°C to 20.0°C | Mean = 14.2°C
\n Ground Frost: 2.0 | Relative Humidity: 55.6%
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\n Location: (31.6061, -2.2014)
\n Soil Properties:
\n N: 77.0 | P: 36.0 | K: 23.0 | pH: 6.65 | EC: 0.9
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: HYPER ARID
\n Precipitation (mm): Monthly = 13.0 | Daily = 0.0
\n Precipitation Coefficient of Variation: 121.0
\n Wet Days: 2.8
\n Temperature: 8.5°C to 20.0°C | Mean = 14.2°C
\n Ground Frost: 2.0 | Relative Humidity: 55.6%
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\n Location: (31.6066, -2.2005)
\n Soil Properties:
\n N: 87.0 | P: 60.0 | K: 23.0 | pH: 6.44 | EC: 1.2
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: HYPER ARID
\n Precipitation (mm): Monthly = 13.0 | Daily = 0.0
\n Precipitation Coefficient of Variation: 121.0
\n Wet Days: 2.8
\n Temperature: 8.5°C to 20.0°C | Mean = 14.2°C
\n Ground Frost: 2.0 | Relative Humidity: 55.6%
\n " } }, "9cda84f9efd548bfbbd577382f929d2f": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_5b68d236f4f7443a84a22f4877e32f9e", "placeholder": "​", "style": "IPY_MODEL_bdb6c2ae97df4785bf4f9584efacd313", "value": "\n
\n Location: (31.6078, -2.2006)
\n Soil Properties:
\n N: 60.0 | P: 38.0 | K: 17.0 | pH: 6.47 | EC: 1.2
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: HYPER ARID
\n Precipitation (mm): Monthly = 13.0 | Daily = 0.0
\n Precipitation Coefficient of Variation: 121.0
\n Wet Days: 2.8
\n Temperature: 8.5°C to 20.0°C | Mean = 14.2°C
\n Ground Frost: 2.0 | Relative Humidity: 55.6%
\n " } }, "a281cf1458a5459a91c582d25ed9a657": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_588e6873c09f4c89abebc18a8fa6c23d", "placeholder": "​", "style": "IPY_MODEL_bf2ca4d1a1e44550a41b9c95c138858b", "value": "\n
\n Location: (31.6083, -2.2048)
\n Soil Properties:
\n N: 84.0 | P: 44.0 | K: 21.0 | pH: 5.85 | EC: 1.2
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: HYPER ARID
\n Precipitation (mm): Monthly = 13.0 | Daily = 0.0
\n Precipitation Coefficient of Variation: 121.0
\n Wet Days: 2.8
\n Temperature: 8.5°C to 20.0°C | Mean = 14.2°C
\n Ground Frost: 2.0 | Relative Humidity: 55.6%
\n " } }, "edd3107f80e643b7a65aabdd85f19212": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_af6c7484de6943428458e4e1602923dd", "placeholder": "​", "style": "IPY_MODEL_a851f635a92044dd9a3229860be8f221", "value": "\n
\n Location: (31.6083, -2.2042)
\n Soil Properties:
\n N: 95.0 | P: 38.0 | K: 22.0 | pH: 5.73 | EC: 0.88
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: HYPER ARID
\n Precipitation (mm): Monthly = 13.0 | Daily = 0.0
\n Precipitation Coefficient of Variation: 121.0
\n Wet Days: 2.8
\n Temperature: 8.5°C to 20.0°C | Mean = 14.2°C
\n Ground Frost: 2.0 | Relative Humidity: 55.6%
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\n Location: (31.6089, -2.2039)
\n Soil Properties:
\n N: 94.0 | P: 54.0 | K: 17.0 | pH: 5.87 | EC: 1.2
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: HYPER ARID
\n Precipitation (mm): Monthly = 13.0 | Daily = 0.0
\n Precipitation Coefficient of Variation: 121.0
\n Wet Days: 2.8
\n Temperature: 8.5°C to 20.0°C | Mean = 14.2°C
\n Ground Frost: 2.0 | Relative Humidity: 55.6%
\n " } }, "3fe249c2340a482cb1c0b43b9368d24c": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_711b5c5bb617419ea38bdd7821fba3fb", "placeholder": "​", "style": "IPY_MODEL_93553d0ae39149a6ba18b6592662edf3", "value": "\n
\n Location: (33.2281, 6.7971)
\n Soil Properties:
\n N: 94.0 | P: 50.0 | K: 19.0 | pH: 5.87 | EC: 0.7
\n Soil Type: RG
\n Climate Properties:
\n Bioclimatic Stage: ARID
\n Precipitation (mm): Monthly = 9.0 | Daily = 0.0
\n Precipitation Coefficient of Variation: 111.7
\n Wet Days: 1.6
\n Temperature: 10.0°C to 22.0°C | Mean = 16.0°C
\n Ground Frost: 1.0 | Relative Humidity: 62.1%
\n " } }, "6c51f2b6d5574325bd1ac66cafe4d33c": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_2c4a4d02f9364f869d620fc75e99dc9f", "placeholder": "​", "style": "IPY_MODEL_da38c97967364f1ba9d02239bc7d46df", "value": "\n
\n Location: (33.2293, 6.7806)
\n Soil Properties:
\n N: 96.0 | P: 54.0 | K: 22.0 | pH: 6.96 | EC: 0.88
\n Soil Type: RG
\n Climate Properties:
\n Bioclimatic Stage: ARID
\n Precipitation (mm): Monthly = 9.0 | Daily = 0.0
\n Precipitation Coefficient of Variation: 111.7
\n Wet Days: 1.6
\n Temperature: 10.0°C to 22.0°C | Mean = 16.0°C
\n Ground Frost: 1.0 | Relative Humidity: 62.1%
\n " } }, "0ace6ee70b654843851d1ec66ed0eba1": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_ad4f4b09e4274b6983ec644a86378c54", "placeholder": "​", "style": "IPY_MODEL_39acd0ec301843c6b5fee7bfea4f35b2", "value": "\n
\n Location: (33.2308, 6.7485)
\n Soil Properties:
\n N: 76.0 | P: 39.0 | K: 24.0 | pH: 7.00 | EC: 1.0
\n Soil Type: RG
\n Climate Properties:
\n Bioclimatic Stage: ARID
\n Precipitation (mm): Monthly = 9.0 | Daily = 0.0
\n Precipitation Coefficient of Variation: 111.7
\n Wet Days: 1.6
\n Temperature: 10.0°C to 22.0°C | Mean = 16.0°C
\n Ground Frost: 1.0 | Relative Humidity: 62.1%
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\n Location: (33.2311, 6.7825)
\n Soil Properties:
\n N: 99.0 | P: 39.0 | K: 18.0 | pH: 6.11 | EC: 0.88
\n Soil Type: RG
\n Climate Properties:
\n Bioclimatic Stage: ARID
\n Precipitation (mm): Monthly = 9.0 | Daily = 0.0
\n Precipitation Coefficient of Variation: 111.7
\n Wet Days: 1.6
\n Temperature: 10.0°C to 22.0°C | Mean = 16.0°C
\n Ground Frost: 1.0 | Relative Humidity: 62.1%
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\n Location: (33.2569, 6.7722)
\n Soil Properties:
\n N: 62.0 | P: 48.0 | K: 20.0 | pH: 6.71 | EC: 0.9
\n Soil Type: RG
\n Climate Properties:
\n Bioclimatic Stage: ARID
\n Precipitation (mm): Monthly = 9.0 | Daily = 0.0
\n Precipitation Coefficient of Variation: 111.7
\n Wet Days: 1.6
\n Temperature: 10.0°C to 22.0°C | Mean = 16.0°C
\n Ground Frost: 1.0 | Relative Humidity: 62.1%
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\n Location: (33.2724, 6.8012)
\n Soil Properties:
\n N: 86.0 | P: 37.0 | K: 16.0 | pH: 5.56 | EC: 1.2
\n Soil Type: RG
\n Climate Properties:
\n Bioclimatic Stage: ARID
\n Precipitation (mm): Monthly = 9.0 | Daily = 0.0
\n Precipitation Coefficient of Variation: 111.7
\n Wet Days: 1.6
\n Temperature: 10.0°C to 22.0°C | Mean = 16.0°C
\n Ground Frost: 1.0 | Relative Humidity: 62.1%
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\n Location: (33.3022, 6.8534)
\n Soil Properties:
\n N: 81.0 | P: 49.0 | K: 20.0 | pH: 5.51 | EC: 0.88
\n Soil Type: RG
\n Climate Properties:
\n Bioclimatic Stage: ARID
\n Precipitation (mm): Monthly = 9.0 | Daily = 0.0
\n Precipitation Coefficient of Variation: 111.7
\n Wet Days: 1.6
\n Temperature: 10.0°C to 22.0°C | Mean = 16.0°C
\n Ground Frost: 1.0 | Relative Humidity: 62.1%
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\n Location: (33.3052, 6.8578)
\n Soil Properties:
\n N: 74.0 | P: 39.0 | K: 23.0 | pH: 6.78 | EC: 0.9
\n Soil Type: RG
\n Climate Properties:
\n Bioclimatic Stage: ARID
\n Precipitation (mm): Monthly = 9.0 | Daily = 0.0
\n Precipitation Coefficient of Variation: 111.7
\n Wet Days: 1.6
\n Temperature: 10.0°C to 22.0°C | Mean = 16.0°C
\n Ground Frost: 1.0 | Relative Humidity: 62.1%
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\n Location: (33.3065, 6.8587)
\n Soil Properties:
\n N: 77.0 | P: 52.0 | K: 17.0 | pH: 5.71 | EC: 0.9
\n Soil Type: RG
\n Climate Properties:
\n Bioclimatic Stage: ARID
\n Precipitation (mm): Monthly = 9.0 | Daily = 0.0
\n Precipitation Coefficient of Variation: 111.7
\n Wet Days: 1.6
\n Temperature: 10.0°C to 22.0°C | Mean = 16.0°C
\n Ground Frost: 1.0 | Relative Humidity: 62.1%
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\n Location: (33.3375, 6.8875)
\n Soil Properties:
\n N: 73.0 | P: 45.0 | K: 21.0 | pH: 6.64 | EC: 1.2
\n Soil Type: RG
\n Climate Properties:
\n Bioclimatic Stage: ARID
\n Precipitation (mm): Monthly = 9.0 | Daily = 0.0
\n Precipitation Coefficient of Variation: 111.7
\n Wet Days: 1.6
\n Temperature: 10.0°C to 22.0°C | Mean = 16.0°C
\n Ground Frost: 1.0 | Relative Humidity: 62.1%
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\n Location: (33.3485, 6.8770)
\n Soil Properties:
\n N: 81.0 | P: 45.0 | K: 23.0 | pH: 6.19 | EC: 1.0
\n Soil Type: RG
\n Climate Properties:
\n Bioclimatic Stage: ARID
\n Precipitation (mm): Monthly = 9.0 | Daily = 0.0
\n Precipitation Coefficient of Variation: 111.7
\n Wet Days: 1.6
\n Temperature: 10.0°C to 22.0°C | Mean = 16.0°C
\n Ground Frost: 1.0 | Relative Humidity: 62.1%
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\n Location: (33.3633, 6.8810)
\n Soil Properties:
\n N: 71.0 | P: 35.0 | K: 24.0 | pH: 5.83 | EC: 0.7
\n Soil Type: RG
\n Climate Properties:
\n Bioclimatic Stage: ARID
\n Precipitation (mm): Monthly = 9.0 | Daily = 0.0
\n Precipitation Coefficient of Variation: 111.7
\n Wet Days: 1.6
\n Temperature: 10.0°C to 22.0°C | Mean = 16.0°C
\n Ground Frost: 1.0 | Relative Humidity: 62.1%
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\n Location: (35.1230, -0.6051)
\n Soil Properties:
\n N: 67.0 | P: 60.0 | K: 25.0 | pH: 5.75 | EC: 0.8799999999999999
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SEMI ARID
\n Precipitation (mm): Monthly = 49.0 | Daily = 2.0
\n Precipitation Coefficient of Variation: 78.7
\n Wet Days: 7.0
\n Temperature: 8.0°C to 18.4°C | Mean = 13.2°C
\n Ground Frost: 3.2 | Relative Humidity: 68.1%
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\n Location: (35.1260, -0.6431)
\n Soil Properties:
\n N: 70.0 | P: 44.0 | K: 19.0 | pH: 5.85 | EC: 0.9
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SEMI ARID
\n Precipitation (mm): Monthly = 49.0 | Daily = 2.0
\n Precipitation Coefficient of Variation: 78.7
\n Wet Days: 7.0
\n Temperature: 8.0°C to 18.4°C | Mean = 13.2°C
\n Ground Frost: 3.2 | Relative Humidity: 68.1%
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\n Location: (35.1467, -0.6105)
\n Soil Properties:
\n N: 76.0 | P: 44.0 | K: 17.0 | pH: 5.86 | EC: 0.7
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SEMI ARID
\n Precipitation (mm): Monthly = 49.0 | Daily = 2.0
\n Precipitation Coefficient of Variation: 78.7
\n Wet Days: 7.0
\n Temperature: 8.0°C to 18.4°C | Mean = 13.2°C
\n Ground Frost: 3.2 | Relative Humidity: 68.1%
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\n Location: (35.1504, -0.6377)
\n Soil Properties:
\n N: 89.0 | P: 60.0 | K: 19.0 | pH: 5.91 | EC: 0.8799999999999999
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SEMI ARID
\n Precipitation (mm): Monthly = 49.0 | Daily = 2.0
\n Precipitation Coefficient of Variation: 78.7
\n Wet Days: 7.0
\n Temperature: 8.0°C to 18.4°C | Mean = 13.2°C
\n Ground Frost: 3.2 | Relative Humidity: 68.1%
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\n Location: (35.1638, -0.6277)
\n Soil Properties:
\n N: 93.0 | P: 41.0 | K: 17.0 | pH: 6.05 | EC: 0.9
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SEMI ARID
\n Precipitation (mm): Monthly = 49.0 | Daily = 2.0
\n Precipitation Coefficient of Variation: 78.7
\n Wet Days: 7.0
\n Temperature: 8.0°C to 18.4°C | Mean = 13.2°C
\n Ground Frost: 3.2 | Relative Humidity: 68.1%
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\n Location: (35.4529, -0.5471)
\n Soil Properties:
\n N: 66.0 | P: 54.0 | K: 21.0 | pH: 5.92 | EC: 1.2
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SEMI ARID
\n Precipitation (mm): Monthly = 7.0 | Daily = 0.0
\n Precipitation Coefficient of Variation: 115.1
\n Wet Days: 1.1
\n Temperature: 10.2°C to 23.1°C | Mean = 16.6°C
\n Ground Frost: 0.6 | Relative Humidity: 57.7%
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\n Location: (35.4551, -0.5444)
\n Soil Properties:
\n N: 92.0 | P: 44.0 | K: 16.0 | pH: 6.08 | EC: 0.88
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SEMI ARID
\n Precipitation (mm): Monthly = 7.0 | Daily = 0.0
\n Precipitation Coefficient of Variation: 115.1
\n Wet Days: 1.1
\n Temperature: 10.2°C to 23.1°C | Mean = 16.6°C
\n Ground Frost: 0.6 | Relative Humidity: 57.7%
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\n Location: (35.4573, -0.5371)
\n Soil Properties:
\n N: 62.0 | P: 52.0 | K: 16.0 | pH: 6.97 | EC: 0.7
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SEMI ARID
\n Precipitation (mm): Monthly = 7.0 | Daily = 0.0
\n Precipitation Coefficient of Variation: 115.1
\n Wet Days: 1.1
\n Temperature: 10.2°C to 23.1°C | Mean = 16.6°C
\n Ground Frost: 0.6 | Relative Humidity: 57.7%
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\n Location: (35.4625, -0.5272)
\n Soil Properties:
\n N: 90.0 | P: 49.0 | K: 21.0 | pH: 6.47 | EC: 0.88
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SEMI ARID
\n Precipitation (mm): Monthly = 7.0 | Daily = 0.0
\n Precipitation Coefficient of Variation: 115.1
\n Wet Days: 1.1
\n Temperature: 10.2°C to 23.1°C | Mean = 16.6°C
\n Ground Frost: 0.6 | Relative Humidity: 57.7%
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\n Location: (35.5439, -0.4399)
\n Soil Properties:
\n N: 61.0 | P: 41.0 | K: 17.0 | pH: 6.02 | EC: 1.2
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SEMI ARID
\n Precipitation (mm): Monthly = 7.0 | Daily = 0.0
\n Precipitation Coefficient of Variation: 115.1
\n Wet Days: 1.1
\n Temperature: 10.2°C to 23.1°C | Mean = 16.6°C
\n Ground Frost: 0.6 | Relative Humidity: 57.7%
\n " } }, "a67182896c3a4a11b8e3720455b52841": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_11e289e5eac0439d883f98a9e32df956", "placeholder": "​", "style": "IPY_MODEL_0a75af2ced1a4d56856a90c8713b44c5", "value": "\n
\n Location: (35.5450, -0.4386)
\n Soil Properties:
\n N: 70.0 | P: 47.0 | K: 17.0 | pH: 6.60 | EC: 1.2
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SEMI ARID
\n Precipitation (mm): Monthly = 7.0 | Daily = 0.0
\n Precipitation Coefficient of Variation: 115.1
\n Wet Days: 1.1
\n Temperature: 10.2°C to 23.1°C | Mean = 16.6°C
\n Ground Frost: 0.6 | Relative Humidity: 57.7%
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\n Location: (35.5461, -0.4402)
\n Soil Properties:
\n N: 63.0 | P: 58.0 | K: 22.0 | pH: 6.20 | EC: 0.88
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SEMI ARID
\n Precipitation (mm): Monthly = 7.0 | Daily = 0.0
\n Precipitation Coefficient of Variation: 115.1
\n Wet Days: 1.1
\n Temperature: 10.2°C to 23.1°C | Mean = 16.6°C
\n Ground Frost: 0.6 | Relative Humidity: 57.7%
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\n Location: (35.6931, -0.5088)
\n Soil Properties:
\n N: 74.0 | P: 55.0 | K: 19.0 | pH: 6.29 | EC: 0.9
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SEMI ARID
\n Precipitation (mm): Monthly = 7.0 | Daily = 0.0
\n Precipitation Coefficient of Variation: 115.1
\n Wet Days: 1.1
\n Temperature: 10.2°C to 23.1°C | Mean = 16.6°C
\n Ground Frost: 0.6 | Relative Humidity: 57.7%
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\n Location: (35.6932, -0.5088)
\n Soil Properties:
\n N: 66.0 | P: 53.0 | K: 19.0 | pH: 6.03 | EC: 0.9
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SEMI ARID
\n Precipitation (mm): Monthly = 7.0 | Daily = 0.0
\n Precipitation Coefficient of Variation: 115.1
\n Wet Days: 1.1
\n Temperature: 10.2°C to 23.1°C | Mean = 16.6°C
\n Ground Frost: 0.6 | Relative Humidity: 57.7%
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\n Location: (35.6935, -0.5094)
\n Soil Properties:
\n N: 77.0 | P: 57.0 | K: 21.0 | pH: 6.55 | EC: 1.2
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SEMI ARID
\n Precipitation (mm): Monthly = 7.0 | Daily = 0.0
\n Precipitation Coefficient of Variation: 115.1
\n Wet Days: 1.1
\n Temperature: 10.2°C to 23.1°C | Mean = 16.6°C
\n Ground Frost: 0.6 | Relative Humidity: 57.7%
\n " } }, "6d8a271a255e4c48a8de2bc28ca3ace6": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_e7a67f3332624354b36c4594d28c566f", "placeholder": "​", "style": "IPY_MODEL_265b6e0982644e5fb7ed93ac5e85c79d", "value": "\n
\n Location: (35.6936, -0.5103)
\n Soil Properties:
\n N: 99.0 | P: 50.0 | K: 15.0 | pH: 5.57 | EC: 0.88
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SEMI ARID
\n Precipitation (mm): Monthly = 7.0 | Daily = 0.0
\n Precipitation Coefficient of Variation: 115.1
\n Wet Days: 1.1
\n Temperature: 10.2°C to 23.1°C | Mean = 16.6°C
\n Ground Frost: 0.6 | Relative Humidity: 57.7%
\n " } }, "6f792f7cd90542d8a83d966185b05d5c": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_51c199084a2e49c7a0df7e2028be38e1", "placeholder": "​", "style": "IPY_MODEL_045b5bd8e8df49289b141e7d8c58c3f1", "value": "\n
\n Location: (35.7178, -0.5556)
\n Soil Properties:
\n N: 74.0 | P: 56.0 | K: 22.0 | pH: 6.83 | EC: 1.2
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SEMI ARID
\n Precipitation (mm): Monthly = 7.0 | Daily = 0.0
\n Precipitation Coefficient of Variation: 115.1
\n Wet Days: 1.1
\n Temperature: 10.2°C to 23.1°C | Mean = 16.6°C
\n Ground Frost: 0.6 | Relative Humidity: 57.7%
\n " } }, "6b28dbd11d8d43d69f08c0555948c25f": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_e0d15a7a2ed043f1b5d6eb9664729494", "placeholder": "​", "style": "IPY_MODEL_f4ed2672c49e4a4ea6b51376fbb84942", "value": "\n
\n Location: (35.7182, -0.5554)
\n Soil Properties:
\n N: 83.0 | P: 45.0 | K: 21.0 | pH: 5.72 | EC: 1.2
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SEMI ARID
\n Precipitation (mm): Monthly = 7.0 | Daily = 0.0
\n Precipitation Coefficient of Variation: 115.1
\n Wet Days: 1.1
\n Temperature: 10.2°C to 23.1°C | Mean = 16.6°C
\n Ground Frost: 0.6 | Relative Humidity: 57.7%
\n " } }, "949f848bb307486d883bc445c38cdb77": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_91bc74bd377147f2a89cef6a477930f4", "placeholder": "​", "style": "IPY_MODEL_91064309a13d4b4e96c7aa3eb2b3f33d", "value": "\n
\n Location: (35.7201, -0.5640)
\n Soil Properties:
\n N: 100.0 | P: 48.0 | K: 16.0 | pH: 5.55 | EC: 1.2
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SEMI ARID
\n Precipitation (mm): Monthly = 7.0 | Daily = 0.0
\n Precipitation Coefficient of Variation: 115.1
\n Wet Days: 1.1
\n Temperature: 10.2°C to 23.1°C | Mean = 16.6°C
\n Ground Frost: 0.6 | Relative Humidity: 57.7%
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\n Location: (35.7204, -0.5646)
\n Soil Properties:
\n N: 79.0 | P: 51.0 | K: 16.0 | pH: 6.59 | EC: 1.2
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SEMI ARID
\n Precipitation (mm): Monthly = 7.0 | Daily = 0.0
\n Precipitation Coefficient of Variation: 115.1
\n Wet Days: 1.1
\n Temperature: 10.2°C to 23.1°C | Mean = 16.6°C
\n Ground Frost: 0.6 | Relative Humidity: 57.7%
\n " } }, "771ffe61110640ee9055ece740abaec3": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_2ce2e33954e3414dac9a1809414beb14", "placeholder": "​", "style": "IPY_MODEL_069ee6fd32e144cdba20b0ea8b500c7f", "value": "\n
\n Location: (35.7254, -0.5646)
\n Soil Properties:
\n N: 94.0 | P: 39.0 | K: 18.0 | pH: 5.89 | EC: 0.7
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SEMI ARID
\n Precipitation (mm): Monthly = 7.0 | Daily = 0.0
\n Precipitation Coefficient of Variation: 115.1
\n Wet Days: 1.1
\n Temperature: 10.2°C to 23.1°C | Mean = 16.6°C
\n Ground Frost: 0.6 | Relative Humidity: 57.7%
\n " } }, "939c148797d2409eb0f15434f885a6a2": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_f6f3f0efed9c4281a8d4ab5d7df31aa4", "placeholder": "​", "style": "IPY_MODEL_0a2099e5327846b8a4f828fa18f18d24", "value": "\n
\n Location: (35.8897, 0.0626)
\n Soil Properties:
\n N: 87.0 | P: 54.0 | K: 20.0 | pH: 6.58 | EC: 0.88
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SEMI ARID
\n Precipitation (mm): Monthly = 47.0 | Daily = 2.0
\n Precipitation Coefficient of Variation: 81.0
\n Wet Days: 7.6
\n Temperature: 9.4°C to 20.0°C | Mean = 14.7°C
\n Ground Frost: 1.6 | Relative Humidity: 69.5%
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\n Location: (35.8917, 0.0647)
\n Soil Properties:
\n N: 78.0 | P: 48.0 | K: 22.0 | pH: 5.59 | EC: 0.88
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SEMI ARID
\n Precipitation (mm): Monthly = 47.0 | Daily = 2.0
\n Precipitation Coefficient of Variation: 81.0
\n Wet Days: 7.6
\n Temperature: 9.4°C to 20.0°C | Mean = 14.7°C
\n Ground Frost: 1.6 | Relative Humidity: 69.5%
\n " } }, "efd2e7d808b241f58f6cce98e978bfa0": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_73537f7a854a4c45ad009e81951c79ef", "placeholder": "​", "style": "IPY_MODEL_273f109d5d11482d945a386e1ce9404b", "value": "\n
\n Location: (35.8923, 0.0637)
\n Soil Properties:
\n N: 87.0 | P: 35.0 | K: 25.0 | pH: 6.18 | EC: 0.88
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SEMI ARID
\n Precipitation (mm): Monthly = 47.0 | Daily = 2.0
\n Precipitation Coefficient of Variation: 81.0
\n Wet Days: 7.6
\n Temperature: 9.4°C to 20.0°C | Mean = 14.7°C
\n Ground Frost: 1.6 | Relative Humidity: 69.5%
\n " } }, "731e301ecd09400193c7250b91e497f7": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_89ef8076b0d747fbb383a350f948ff94", "placeholder": "​", "style": "IPY_MODEL_921279445bb048e1a0103dc9a525e0ba", "value": "\n
\n Location: (35.8927, 0.0669)
\n Soil Properties:
\n N: 75.0 | P: 49.0 | K: 15.0 | pH: 5.92 | EC: 1.2
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SEMI ARID
\n Precipitation (mm): Monthly = 47.0 | Daily = 2.0
\n Precipitation Coefficient of Variation: 81.0
\n Wet Days: 7.6
\n Temperature: 9.4°C to 20.0°C | Mean = 14.7°C
\n Ground Frost: 1.6 | Relative Humidity: 69.5%
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\n Location: (35.9517, 0.1251)
\n Soil Properties:
\n N: 63.0 | P: 43.0 | K: 19.0 | pH: 6.64 | EC: 1.2
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SEMI ARID
\n Precipitation (mm): Monthly = 47.0 | Daily = 2.0
\n Precipitation Coefficient of Variation: 81.0
\n Wet Days: 7.6
\n Temperature: 9.4°C to 20.0°C | Mean = 14.7°C
\n Ground Frost: 1.6 | Relative Humidity: 69.5%
\n " } }, "f2f2ae4ea80447ca9bbd2d8f3bb644d5": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_b54e47ba4d934d4e92149ee14fd6446e", "placeholder": "​", "style": "IPY_MODEL_ea052ba094a8476ba284c89ff99228ca", "value": "\n
\n Location: (35.9531, 0.1270)
\n Soil Properties:
\n N: 84.0 | P: 57.0 | K: 25.0 | pH: 6.49 | EC: 0.88
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SEMI ARID
\n Precipitation (mm): Monthly = 47.0 | Daily = 2.0
\n Precipitation Coefficient of Variation: 81.0
\n Wet Days: 7.6
\n Temperature: 9.4°C to 20.0°C | Mean = 14.7°C
\n Ground Frost: 1.6 | Relative Humidity: 69.5%
\n " } }, "5e1cd722b40b4ab8a209f5bbdf8920ff": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_9c125f5f44f84ff39c2e488a3c54df30", "placeholder": "​", "style": "IPY_MODEL_1c0789fc99814a86b52e951d15799475", "value": "\n
\n Location: (35.9544, 0.1270)
\n Soil Properties:
\n N: 64.0 | P: 35.0 | K: 23.0 | pH: 5.68 | EC: 1.2
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SEMI ARID
\n Precipitation (mm): Monthly = 47.0 | Daily = 2.0
\n Precipitation Coefficient of Variation: 81.0
\n Wet Days: 7.6
\n Temperature: 9.4°C to 20.0°C | Mean = 14.7°C
\n Ground Frost: 1.6 | Relative Humidity: 69.5%
\n " } }, "3d01b6bc3dd34787a3857b460f50452d": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_41156aaf85114d8f82c5b8153e77667e", "placeholder": "​", "style": "IPY_MODEL_d07edff0019d494d94f80e58fc98d8d7", "value": "\n
\n Location: (35.9549, 0.1270)
\n Soil Properties:
\n N: 60.0 | P: 46.0 | K: 22.0 | pH: 6.63 | EC: 0.9000000000000001
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SEMI ARID
\n Precipitation (mm): Monthly = 47.0 | Daily = 2.0
\n Precipitation Coefficient of Variation: 81.0
\n Wet Days: 7.6
\n Temperature: 9.4°C to 20.0°C | Mean = 14.7°C
\n Ground Frost: 1.6 | Relative Humidity: 69.5%
\n " } }, "25c3019402cd45eea901bf4dc305976c": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_830b2290c4774784a4aa5cbcf1ba847e", "placeholder": "​", "style": "IPY_MODEL_f18d199068c54427b61fcf9f0c8efa0e", "value": "\n
\n Location: (36.3467, 4.2804)
\n Soil Properties:
\n N: 74.0 | P: 43.0 | K: 23.0 | pH: 6.33 | EC: 0.88
\n Soil Type: CM
\n Climate Properties:
\n Bioclimatic Stage: ARID
\n Precipitation (mm): Monthly = 77.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 71.0
\n Wet Days: 10.1
\n Temperature: 7.6°C to 16.7°C | Mean = 12.1°C
\n Ground Frost: 4.6 | Relative Humidity: 71.6%
\n " } }, "94a9d00c6f1141699b0348d11047c4b2": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_8a76fa4f56b049c1b30d88261315012c", "placeholder": "​", "style": "IPY_MODEL_faaed45bf82545539906ad20a8c137fa", "value": "\n
\n Location: (36.3477, 4.2814)
\n Soil Properties:
\n N: 74.0 | P: 58.0 | K: 18.0 | pH: 6.73 | EC: 1.0
\n Soil Type: CM
\n Climate Properties:
\n Bioclimatic Stage: ARID
\n Precipitation (mm): Monthly = 77.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 71.0
\n Wet Days: 10.1
\n Temperature: 7.6°C to 16.7°C | Mean = 12.1°C
\n Ground Frost: 4.6 | Relative Humidity: 71.6%
\n " } }, "650ea4e41110431eb770cdd0caa01ee2": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_609e7d6696e64648aa679b991c00392d", "placeholder": "​", "style": "IPY_MODEL_28d81f8c27ee443bb3c46894f5b8461a", "value": "\n
\n Location: (36.3486, 4.2776)
\n Soil Properties:
\n N: 74.0 | P: 48.0 | K: 17.0 | pH: 6.43 | EC: 0.88
\n Soil Type: CM
\n Climate Properties:
\n Bioclimatic Stage: ARID
\n Precipitation (mm): Monthly = 77.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 71.0
\n Wet Days: 10.1
\n Temperature: 7.6°C to 16.7°C | Mean = 12.1°C
\n Ground Frost: 4.6 | Relative Humidity: 71.6%
\n " } }, "23d489a6d2ef4503937a8c34aaf77865": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_3ba94bb4bcf04dffaa605771c2645472", "placeholder": "​", "style": "IPY_MODEL_1f010e4a24a3454888e2c1a97eb849fc", "value": "\n
\n Location: (36.3490, 4.2799)
\n Soil Properties:
\n N: 61.0 | P: 60.0 | K: 15.0 | pH: 6.27 | EC: 0.7
\n Soil Type: CM
\n Climate Properties:
\n Bioclimatic Stage: ARID
\n Precipitation (mm): Monthly = 77.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 71.0
\n Wet Days: 10.1
\n Temperature: 7.6°C to 16.7°C | Mean = 12.1°C
\n Ground Frost: 4.6 | Relative Humidity: 71.6%
\n " } }, "4059551e26de4eaf911ee6641ba1707b": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_915daf3759a3485f9893edb8f35d104e", "placeholder": "​", "style": "IPY_MODEL_5bf01efcb93b4b9bb177d24e88be4caa", "value": "\n
\n Location: (36.3498, 4.2775)
\n Soil Properties:
\n N: 60.0 | P: 44.0 | K: 23.0 | pH: 5.72 | EC: 0.88
\n Soil Type: CM
\n Climate Properties:
\n Bioclimatic Stage: ARID
\n Precipitation (mm): Monthly = 77.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 71.0
\n Wet Days: 10.1
\n Temperature: 7.6°C to 16.7°C | Mean = 12.1°C
\n Ground Frost: 4.6 | Relative Humidity: 71.6%
\n " } }, "eb8b123c4d064958b54faadb80984e75": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_cdb92737cc724966896c9776300d0c2d", "placeholder": "​", "style": "IPY_MODEL_416b47c4353d4579b89b803499af869c", "value": "\n
\n Location: (36.3500, 4.2769)
\n Soil Properties:
\n N: 89.0 | P: 60.0 | K: 17.0 | pH: 5.98 | EC: 0.88
\n Soil Type: CM
\n Climate Properties:
\n Bioclimatic Stage: ARID
\n Precipitation (mm): Monthly = 77.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 71.0
\n Wet Days: 10.1
\n Temperature: 7.6°C to 16.7°C | Mean = 12.1°C
\n Ground Frost: 4.6 | Relative Humidity: 71.6%
\n " } }, "510a9d57dc524ea89cedd7132bd63595": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_22e194df1057442d845a0d44fcb2e455", "placeholder": "​", "style": "IPY_MODEL_ebacb51bd2f84ef5ac49e719e8436cb4", "value": "\n
\n Location: (36.3502, 4.2804)
\n Soil Properties:
\n N: 96.0 | P: 46.0 | K: 22.0 | pH: 6.50 | EC: 1.2
\n Soil Type: CM
\n Climate Properties:
\n Bioclimatic Stage: ARID
\n Precipitation (mm): Monthly = 77.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 71.0
\n Wet Days: 10.1
\n Temperature: 7.6°C to 16.7°C | Mean = 12.1°C
\n Ground Frost: 4.6 | Relative Humidity: 71.6%
\n " } }, "15e0d7e09305487bbc79d41fffceecf5": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_a02c167dbe1e4b689cf7e0f6b781111f", "placeholder": "​", "style": "IPY_MODEL_221d8638ef25432790ecbc4efe75c48e", "value": "\n
\n Location: (36.3507, 4.2784)
\n Soil Properties:
\n N: 69.0 | P: 51.0 | K: 23.0 | pH: 6.80 | EC: 0.7
\n Soil Type: CM
\n Climate Properties:
\n Bioclimatic Stage: ARID
\n Precipitation (mm): Monthly = 77.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 71.0
\n Wet Days: 10.1
\n Temperature: 7.6°C to 16.7°C | Mean = 12.1°C
\n Ground Frost: 4.6 | Relative Humidity: 71.6%
\n " } }, "055e4593b2a745f5a85b274bcb224419": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_b6a995fc1bbc4b85a822d9eefe4f0775", "placeholder": "​", "style": "IPY_MODEL_aece5286d0124f08baf64a6ddb0e0ba1", "value": "\n
\n Location: (36.5722, 4.2211)
\n Soil Properties:
\n N: 94.0 | P: 50.0 | K: 37.0 | pH: 6.95 | EC: 0.8800000000000001
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SUB HUMID
\n Precipitation (mm): Monthly = 83.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 69.5
\n Wet Days: 10.5
\n Temperature: 8.5°C to 17.6°C | Mean = 13.0°C
\n Ground Frost: 3.5 | Relative Humidity: 72.5%
\n " } }, "ffa2a6ea13fe49b4ae238a5021b38a50": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_aba2a2a138804e56a54be87cf6558454", "placeholder": "​", "style": "IPY_MODEL_e360c8f6b43246acb0d47efb66dd3c21", "value": "\n
\n Location: (36.5752, 4.2211)
\n Soil Properties:
\n N: 86.0 | P: 59.0 | K: 35.0 | pH: 6.95 | EC: 1.2
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SUB HUMID
\n Precipitation (mm): Monthly = 83.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 69.5
\n Wet Days: 10.5
\n Temperature: 8.5°C to 17.6°C | Mean = 13.0°C
\n Ground Frost: 3.5 | Relative Humidity: 72.5%
\n " } }, "0042781e9ba442f4a94b54a5ee6aaf8f": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_1ee2ba15617c4398bcb9fbf08c14ebbc", "placeholder": "​", "style": "IPY_MODEL_1d2aa9fe237744b5af7abffade2bb83b", "value": "\n
\n Location: (36.5812, 4.2235)
\n Soil Properties:
\n N: 85.0 | P: 38.0 | K: 41.0 | pH: 6.25 | EC: 0.8800000000000001
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SUB HUMID
\n Precipitation (mm): Monthly = 83.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 69.5
\n Wet Days: 10.5
\n Temperature: 8.5°C to 17.6°C | Mean = 13.0°C
\n Ground Frost: 3.5 | Relative Humidity: 72.5%
\n " } }, "9bf80a2cc7384a6a87ea47d8328fc1f2": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_a913bb29de9f4eb1a9b418a14fdba85c", "placeholder": "​", "style": "IPY_MODEL_96137e59310940cfbe1221530da8f283", "value": "\n
\n Location: (36.5832, 4.2235)
\n Soil Properties:
\n N: 91.0 | P: 56.0 | K: 37.0 | pH: 6.36 | EC: 0.9
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SUB HUMID
\n Precipitation (mm): Monthly = 83.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 69.5
\n Wet Days: 10.5
\n Temperature: 8.5°C to 17.6°C | Mean = 13.0°C
\n Ground Frost: 3.5 | Relative Humidity: 72.5%
\n " } }, "10074f858db9444f841351e694637ed9": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_ac35f8e9ba064f87a5148c2f4b4e5b2b", "placeholder": "​", "style": "IPY_MODEL_324ba72b41b74eee9fbc5060929cd652", "value": "\n
\n Location: (36.5855, 4.2073)
\n Soil Properties:
\n N: 60.0 | P: 48.0 | K: 39.0 | pH: 7.04 | EC: 0.7
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SUB HUMID
\n Precipitation (mm): Monthly = 83.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 69.5
\n Wet Days: 10.5
\n Temperature: 8.5°C to 17.6°C | Mean = 13.0°C
\n Ground Frost: 3.5 | Relative Humidity: 72.5%
\n " } }, "b66d884f02ee475a8eb0b3ec017a3790": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_57750a5187f544c6b3df9175e66ce3ac", "placeholder": "​", "style": "IPY_MODEL_f1532fea46fa4a1bb8f627284a296c0a", "value": "\n
\n Location: (36.5858, 4.2073)
\n Soil Properties:
\n N: 69.0 | P: 46.0 | K: 41.0 | pH: 5.01 | EC: 0.8800000000000001
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SUB HUMID
\n Precipitation (mm): Monthly = 83.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 69.5
\n Wet Days: 10.5
\n Temperature: 8.5°C to 17.6°C | Mean = 13.0°C
\n Ground Frost: 3.5 | Relative Humidity: 72.5%
\n " } }, "2a16fa44572942cfb0dc7700a045b4be": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_1e5bac7094c242d78ce63fbf84b5027c", "placeholder": "​", "style": "IPY_MODEL_6f40a0d422cb4d009dcf8fe5e6d27bd0", "value": "\n
\n Location: (36.5917, 4.2084)
\n Soil Properties:
\n N: 91.0 | P: 35.0 | K: 39.0 | pH: 6.97 | EC: 0.8800000000000001
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SUB HUMID
\n Precipitation (mm): Monthly = 83.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 69.5
\n Wet Days: 10.5
\n Temperature: 8.5°C to 17.6°C | Mean = 13.0°C
\n Ground Frost: 3.5 | Relative Humidity: 72.5%
\n " } }, "f033105ff4c943d8aa1e4927d2c4bff8": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_3dde8264acb74bfa881269f14f7d2951", "placeholder": "​", "style": "IPY_MODEL_912454c1ca3c4914aa2ca7241d136089", "value": "\n
\n Location: (36.5921, 4.2084)
\n Soil Properties:
\n N: 61.0 | P: 52.0 | K: 41.0 | pH: 6.88 | EC: 1.0
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SUB HUMID
\n Precipitation (mm): Monthly = 83.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 69.5
\n Wet Days: 10.5
\n Temperature: 8.5°C to 17.6°C | Mean = 13.0°C
\n Ground Frost: 3.5 | Relative Humidity: 72.5%
\n " } }, "38c3cfcdba64450cb7dd760c4585eefe": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_b0d406adcf9f41a68c436f2acc17d768", "placeholder": "​", "style": "IPY_MODEL_c1281cc149ca43449327008f238539cf", "value": "\n
\n Location: (36.6310, 5.4661)
\n Soil Properties:
\n N: 89.0 | P: 45.0 | K: 36.0 | pH: 6.44 | EC: 1.2
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SEMI ARID
\n Precipitation (mm): Monthly = 69.0 | Daily = 2.0
\n Precipitation Coefficient of Variation: 69.9
\n Wet Days: 10.9
\n Temperature: 10.7°C to 19.5°C | Mean = 15.099999999999998°C
\n Ground Frost: 1.1 | Relative Humidity: 73.4%
\n " } }, "2224475c5b9f411b98dabaff6298f3b7": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_104d216db1cd46e8b51d6f968b6c07e3", "placeholder": "​", "style": "IPY_MODEL_84a0867e707342f4bba5380b538eda19", "value": "\n
\n Location: (36.6320, 5.4661)
\n Soil Properties:
\n N: 78.0 | P: 43.0 | K: 42.0 | pH: 7.28 | EC: 0.88
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SEMI ARID
\n Precipitation (mm): Monthly = 69.0 | Daily = 2.0
\n Precipitation Coefficient of Variation: 69.9
\n Wet Days: 10.9
\n Temperature: 10.7°C to 19.5°C | Mean = 15.099999999999998°C
\n Ground Frost: 1.1 | Relative Humidity: 73.4%
\n " } }, "94ad01a275184c2aa8cf108f61d1777b": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_ac8c203064bc4ba985a8a2ca7089e1cd", "placeholder": "​", "style": "IPY_MODEL_9dce419e3cbf48b78a25382ea6050570", "value": "\n
\n Location: (36.6381, 5.4834)
\n Soil Properties:
\n N: 75.0 | P: 54.0 | K: 36.0 | pH: 7.02 | EC: 0.7
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SEMI ARID
\n Precipitation (mm): Monthly = 69.0 | Daily = 2.0
\n Precipitation Coefficient of Variation: 69.9
\n Wet Days: 10.9
\n Temperature: 10.7°C to 19.5°C | Mean = 15.099999999999998°C
\n Ground Frost: 1.1 | Relative Humidity: 73.4%
\n " } }, "80a35e842d014557be0cb983887a7c1a": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_757bb2e131374cd7893fd7e8b4e44688", "placeholder": "​", "style": "IPY_MODEL_cdb51ed4b5e944229ead18bd9c3c714d", "value": "\n
\n Location: (36.6391, 5.4834)
\n Soil Properties:
\n N: 76.0 | P: 40.0 | K: 43.0 | pH: 5.07 | EC: 1.2
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SEMI ARID
\n Precipitation (mm): Monthly = 69.0 | Daily = 2.0
\n Precipitation Coefficient of Variation: 69.9
\n Wet Days: 10.9
\n Temperature: 10.7°C to 19.5°C | Mean = 15.099999999999998°C
\n Ground Frost: 1.1 | Relative Humidity: 73.4%
\n " } }, "3405801ba30f4859990cf2f67ce2c421": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_a6f9f858549a44b8930da3267091bf22", "placeholder": "​", "style": "IPY_MODEL_ecd30fc15116497d8cdd761b6caf97f4", "value": "\n
\n Location: (36.6427, 5.4632)
\n Soil Properties:
\n N: 97.0 | P: 36.0 | K: 45.0 | pH: 6.94 | EC: 1.2
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SEMI ARID
\n Precipitation (mm): Monthly = 69.0 | Daily = 2.0
\n Precipitation Coefficient of Variation: 69.9
\n Wet Days: 10.9
\n Temperature: 10.7°C to 19.5°C | Mean = 15.099999999999998°C
\n Ground Frost: 1.1 | Relative Humidity: 73.4%
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\n Location: (36.6437, 5.4632)
\n Soil Properties:
\n N: 67.0 | P: 59.0 | K: 41.0 | pH: 6.01 | EC: 1.2
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SEMI ARID
\n Precipitation (mm): Monthly = 69.0 | Daily = 2.0
\n Precipitation Coefficient of Variation: 69.9
\n Wet Days: 10.9
\n Temperature: 10.7°C to 19.5°C | Mean = 15.099999999999998°C
\n Ground Frost: 1.1 | Relative Humidity: 73.4%
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\n Location: (36.6477, 4.9247)
\n Soil Properties:
\n N: 79.0 | P: 42.0 | K: 37.0 | pH: 6.59 | EC: 0.7
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SEMI ARID
\n Precipitation (mm): Monthly = 69.0 | Daily = 2.0
\n Precipitation Coefficient of Variation: 69.9
\n Wet Days: 10.9
\n Temperature: 10.7°C to 19.5°C | Mean = 15.099999999999998°C
\n Ground Frost: 1.1 | Relative Humidity: 73.4%
\n " } }, "7477affbb1844807ade8348e79bbdde6": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_74f1330983ef4d12879a5e1b71bfdd20", "placeholder": "​", "style": "IPY_MODEL_6c4f87856ebc4ef08446838d21297786", "value": "\n
\n Location: (36.6487, 4.9247)
\n Soil Properties:
\n N: 88.0 | P: 35.0 | K: 40.0 | pH: 5.85 | EC: 1.2
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SEMI ARID
\n Precipitation (mm): Monthly = 69.0 | Daily = 2.0
\n Precipitation Coefficient of Variation: 69.9
\n Wet Days: 10.9
\n Temperature: 10.7°C to 19.5°C | Mean = 15.099999999999998°C
\n Ground Frost: 1.1 | Relative Humidity: 73.4%
\n " } }, "247c7caf82ed49338d3eddebf85d431f": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_a7809a40a8f544a29e2fe731cac62d58", "placeholder": "​", "style": "IPY_MODEL_163bf95351e94f83acd8705821c74bdf", "value": "\n
\n Location: (36.6532, 4.9219)
\n Soil Properties:
\n N: 77.0 | P: 38.0 | K: 36.0 | pH: 5.95 | EC: 0.9
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SEMI ARID
\n Precipitation (mm): Monthly = 69.0 | Daily = 2.0
\n Precipitation Coefficient of Variation: 69.9
\n Wet Days: 10.9
\n Temperature: 10.7°C to 19.5°C | Mean = 15.099999999999998°C
\n Ground Frost: 1.1 | Relative Humidity: 73.4%
\n " } }, "59abf21e6b284e0781f2253ec9a05f41": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_95a2b5ab8a03455d85f89e5aa68a6d96", "placeholder": "​", "style": "IPY_MODEL_eb68f921715b4ea0ac097e9dbacb44d6", "value": "\n
\n Location: (36.6539, 4.9219)
\n Soil Properties:
\n N: 67.0 | P: 45.0 | K: 38.0 | pH: 7.30 | EC: 1.2
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SEMI ARID
\n Precipitation (mm): Monthly = 69.0 | Daily = 2.0
\n Precipitation Coefficient of Variation: 69.9
\n Wet Days: 10.9
\n Temperature: 10.7°C to 19.5°C | Mean = 15.099999999999998°C
\n Ground Frost: 1.1 | Relative Humidity: 73.4%
\n " } }, "e33335eaf7ca4d6b83e632543538a150": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_da1e114e718b47babc1ae3f8d2d0aee5", "placeholder": "​", "style": "IPY_MODEL_a685bc3d8e474bd09d9a8ac56831de5c", "value": "\n
\n Location: (36.7110, 6.4549)
\n Soil Properties:
\n N: 66.0 | P: 53.0 | K: 41.0 | pH: 7.78 | EC: 0.8800000000000001
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: HUMID
\n Precipitation (mm): Monthly = 85.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 65.7
\n Wet Days: 10.9
\n Temperature: 10.5°C to 19.9°C | Mean = 15.200000000000001°C
\n Ground Frost: 1.0 | Relative Humidity: 74.5%
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\n Location: (36.7120, 6.4549)
\n Soil Properties:
\n N: 77.0 | P: 36.0 | K: 37.0 | pH: 6.14 | EC: 1.2
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: HUMID
\n Precipitation (mm): Monthly = 85.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 65.7
\n Wet Days: 10.9
\n Temperature: 10.5°C to 19.9°C | Mean = 15.200000000000001°C
\n Ground Frost: 1.0 | Relative Humidity: 74.5%
\n " } }, "19850786458448209ddd5cf3eb56a09a": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_a0de1b132e3f402e8975cfaf906b9999", "placeholder": "​", "style": "IPY_MODEL_c0242dc029a14990a19e7c1327c9b94e", "value": "\n
\n Location: (36.7121, 6.4462)
\n Soil Properties:
\n N: 83.0 | P: 41.0 | K: 43.0 | pH: 6.25 | EC: 0.7000000000000001
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: HUMID
\n Precipitation (mm): Monthly = 85.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 65.7
\n Wet Days: 10.9
\n Temperature: 10.5°C to 19.9°C | Mean = 15.200000000000001°C
\n Ground Frost: 1.0 | Relative Humidity: 74.5%
\n " } }, "5b3c7a1828c9404f87e03ce24e074b11": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_e42ca97fa2084de1a585dceb25f45f70", "placeholder": "​", "style": "IPY_MODEL_fa25b37c81ea4cb79559589684b8b04b", "value": "\n
\n Location: (36.7131, 6.4462)
\n Soil Properties:
\n N: 67.0 | P: 47.0 | K: 44.0 | pH: 7.87 | EC: 0.7000000000000001
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: HUMID
\n Precipitation (mm): Monthly = 85.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 65.7
\n Wet Days: 10.9
\n Temperature: 10.5°C to 19.9°C | Mean = 15.200000000000001°C
\n Ground Frost: 1.0 | Relative Humidity: 74.5%
\n " } }, "64715d0b3a4648cdafc59d286dd5cc72": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_eb75e459bdf3442696dcfcbab8180c1c", "placeholder": "​", "style": "IPY_MODEL_86a55884a5e14ece91cd4010e046283e", "value": "\n
\n Location: (36.7150, 3.5599)
\n Soil Properties:
\n N: 99.0 | P: 41.0 | K: 36.0 | pH: 6.74 | EC: 0.88
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SUB HUMID
\n Precipitation (mm): Monthly = 91.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 68.4
\n Wet Days: 10.4
\n Temperature: 9.7°C to 19.9°C | Mean = 14.8°C
\n Ground Frost: 1.2 | Relative Humidity: 72.5%
\n " } }, "1ebc4aec45b646039aeb977a75c72e9c": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_cea199bd932649f18d8ec9c68e3cacfe", "placeholder": "​", "style": "IPY_MODEL_fe99cf9f84f94bb59c0be373ec15281a", "value": "\n
\n Location: (36.7151, 3.5472)
\n Soil Properties:
\n N: 76.0 | P: 47.0 | K: 42.0 | pH: 5.74 | EC: 0.7
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SUB HUMID
\n Precipitation (mm): Monthly = 91.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 68.4
\n Wet Days: 10.4
\n Temperature: 9.7°C to 19.9°C | Mean = 14.8°C
\n Ground Frost: 1.2 | Relative Humidity: 72.5%
\n " } }, "c3022b21054a4a19beed9fc9be12baa8": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_dcceb365020b4eca81e957dd55031f9f", "placeholder": "​", "style": "IPY_MODEL_4420ce6990554352b8932d1a4c9f34eb", "value": "\n
\n Location: (36.7160, 3.5599)
\n Soil Properties:
\n N: 78.0 | P: 58.0 | K: 44.0 | pH: 5.11 | EC: 0.7
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SUB HUMID
\n Precipitation (mm): Monthly = 91.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 68.4
\n Wet Days: 10.4
\n Temperature: 9.7°C to 19.9°C | Mean = 14.8°C
\n Ground Frost: 1.2 | Relative Humidity: 72.5%
\n " } }, "640876c6494b4fd59879f8144982a57c": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_3d5d12c2067d49c8be29eaa7d5db67d9", "placeholder": "​", "style": "IPY_MODEL_56a8028e18184d52985f47aaf6e17ec2", "value": "\n
\n Location: (36.7161, 3.5465)
\n Soil Properties:
\n N: 70.0 | P: 36.0 | K: 42.0 | pH: 6.95 | EC: 0.7
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SUB HUMID
\n Precipitation (mm): Monthly = 91.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 68.4
\n Wet Days: 10.4
\n Temperature: 9.7°C to 19.9°C | Mean = 14.8°C
\n Ground Frost: 1.2 | Relative Humidity: 72.5%
\n " } }, "fedfec39a1e8479e8bcf7aacb3883b3f": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_e3db4d08ae1844faa76c6ba4436c1de5", "placeholder": "​", "style": "IPY_MODEL_a8cfb1de4d544303a16a832395dd8053", "value": "\n
\n Location: (36.7171, 3.5465)
\n Soil Properties:
\n N: 91.0 | P: 53.0 | K: 40.0 | pH: 5.39 | EC: 1.0
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SUB HUMID
\n Precipitation (mm): Monthly = 91.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 68.4
\n Wet Days: 10.4
\n Temperature: 9.7°C to 19.9°C | Mean = 14.8°C
\n Ground Frost: 1.2 | Relative Humidity: 72.5%
\n " } }, "47e8341929ee4d94b05110b973179509": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_232e2542bcea4868a8fa0a59ccf192e6", "placeholder": "​", "style": "IPY_MODEL_581a6c381f66439cbff99234f2c8fd22", "value": "\n
\n Location: (36.7184, 4.1250)
\n Soil Properties:
\n N: 93.0 | P: 56.0 | K: 36.0 | pH: 6.98 | EC: 0.9
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SUB HUMID
\n Precipitation (mm): Monthly = 83.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 69.5
\n Wet Days: 10.5
\n Temperature: 8.5°C to 17.6°C | Mean = 13.0°C
\n Ground Frost: 3.5 | Relative Humidity: 72.5%
\n " } }, "bf32af27ec314ed2bda1c13cd971eca1": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_8a87470ab31841a891acafedf07bf1bb", "placeholder": "​", "style": "IPY_MODEL_1284cb7a9a3c4b12945a42771c0c0322", "value": "\n
\n Location: (36.7191, 3.5472)
\n Soil Properties:
\n N: 90.0 | P: 46.0 | K: 42.0 | pH: 7.50 | EC: 1.2
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SUB HUMID
\n Precipitation (mm): Monthly = 91.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 68.4
\n Wet Days: 10.4
\n Temperature: 9.7°C to 19.9°C | Mean = 14.8°C
\n Ground Frost: 1.2 | Relative Humidity: 72.5%
\n " } }, "11edc4ef298243d28cc2d748c98ada7c": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_97b9e959d38244108c4bf369b8348238", "placeholder": "​", "style": "IPY_MODEL_4e71c026f8b747c6a347cd5a1d07e983", "value": "\n
\n Location: (36.7194, 4.1250)
\n Soil Properties:
\n N: 99.0 | P: 54.0 | K: 37.0 | pH: 5.59 | EC: 0.8800000000000001
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SUB HUMID
\n Precipitation (mm): Monthly = 83.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 69.5
\n Wet Days: 10.5
\n Temperature: 8.5°C to 17.6°C | Mean = 13.0°C
\n Ground Frost: 3.5 | Relative Humidity: 72.5%
\n " } }, "3ed7c5a11d60485c8088b8bd5f7ecd0f": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_381597a5e37d4ef788698960132acc60", "placeholder": "​", "style": "IPY_MODEL_399c589b7e2c48189ca96b9dc8f01a5d", "value": "\n
\n Location: (36.7330, 6.4621)
\n Soil Properties:
\n N: 98.0 | P: 47.0 | K: 37.0 | pH: 7.38 | EC: 1.2
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: HUMID
\n Precipitation (mm): Monthly = 85.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 65.7
\n Wet Days: 10.9
\n Temperature: 10.5°C to 19.9°C | Mean = 15.200000000000001°C
\n Ground Frost: 1.0 | Relative Humidity: 74.5%
\n " } }, "9551cfd41ea54a249c550a625e1e51e2": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_cf2832f6804d43929641724fd2a5d373", "placeholder": "​", "style": "IPY_MODEL_36817ce25f9c4944aafdcb64c57354ca", "value": "\n
\n Location: (36.7350, 6.4621)
\n Soil Properties:
\n N: 73.0 | P: 35.0 | K: 38.0 | pH: 5.01 | EC: 0.7000000000000001
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: HUMID
\n Precipitation (mm): Monthly = 85.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 65.7
\n Wet Days: 10.9
\n Temperature: 10.5°C to 19.9°C | Mean = 15.200000000000001°C
\n Ground Frost: 1.0 | Relative Humidity: 74.5%
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\n Location: (36.7364, 3.2867)
\n Soil Properties:
\n N: 65.0 | P: 60.0 | K: 43.0 | pH: 5.66 | EC: 0.9
\n Soil Type: FL
\n Climate Properties:
\n Bioclimatic Stage: SUB HUMID
\n Precipitation (mm): Monthly = 87.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 70.0
\n Wet Days: 10.2
\n Temperature: 9.8°C to 20.1°C | Mean = 14.9°C
\n Ground Frost: 0.8 | Relative Humidity: 72.2%
\n " } }, "b81096ab868f47c4b34adadf53d0db71": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_621849edcac54d5d87dfb9ff4fbc4e4b", "placeholder": "​", "style": "IPY_MODEL_2efc9c844a9e4d208682628920c0db37", "value": "\n
\n Location: (36.7365, 3.2854)
\n Soil Properties:
\n N: 95.0 | P: 52.0 | K: 36.0 | pH: 5.54 | EC: 0.8799999999999999
\n Soil Type: FL
\n Climate Properties:
\n Bioclimatic Stage: SUB HUMID
\n Precipitation (mm): Monthly = 87.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 70.0
\n Wet Days: 10.2
\n Temperature: 9.8°C to 20.1°C | Mean = 14.9°C
\n Ground Frost: 0.8 | Relative Humidity: 72.2%
\n " } }, "e5903f87ab554352946c03de3f663b31": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_aae29d8ad1284c75be3310d41faf3038", "placeholder": "​", "style": "IPY_MODEL_f44870206fe0448abc8e607158ca348e", "value": "\n
\n Location: (36.7377, 3.2864)
\n Soil Properties:
\n N: 75.0 | P: 38.0 | K: 39.0 | pH: 6.22 | EC: 0.8799999999999999
\n Soil Type: FL
\n Climate Properties:
\n Bioclimatic Stage: SUB HUMID
\n Precipitation (mm): Monthly = 87.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 70.0
\n Wet Days: 10.2
\n Temperature: 9.8°C to 20.1°C | Mean = 14.9°C
\n Ground Frost: 0.8 | Relative Humidity: 72.2%
\n " } }, "ed301b3f2c0a4c97ae720483a6c68caf": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_890ce453f9354e11bd292be258342839", "placeholder": "​", "style": "IPY_MODEL_23d04efabe2a4be2a87e6aaeef8cb578", "value": "\n
\n Location: (36.7394, 3.2867)
\n Soil Properties:
\n N: 90.0 | P: 42.0 | K: 43.0 | pH: 6.50 | EC: 0.7
\n Soil Type: FL
\n Climate Properties:
\n Bioclimatic Stage: SUB HUMID
\n Precipitation (mm): Monthly = 87.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 70.0
\n Wet Days: 10.2
\n Temperature: 9.8°C to 20.1°C | Mean = 14.9°C
\n Ground Frost: 0.8 | Relative Humidity: 72.2%
\n " } }, "16f16e243db147a194224744f170d13a": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_61f6eb1575424a85b71f2e4fca5d3569", "placeholder": "​", "style": "IPY_MODEL_19bb78c1250f4eb298750c5b57a052cc", "value": "\n
\n Location: (36.7395, 3.2854)
\n Soil Properties:
\n N: 85.0 | P: 58.0 | K: 41.0 | pH: 7.04 | EC: 1.2
\n Soil Type: FL
\n Climate Properties:
\n Bioclimatic Stage: SUB HUMID
\n Precipitation (mm): Monthly = 87.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 70.0
\n Wet Days: 10.2
\n Temperature: 9.8°C to 20.1°C | Mean = 14.9°C
\n Ground Frost: 0.8 | Relative Humidity: 72.2%
\n " } }, "a8cd0f2a6878431aa6c93f7ab4241cf4": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_bb646f020fb247e382362980c5d9dafe", "placeholder": "​", "style": "IPY_MODEL_a5158c147164495eac1b9ea1ce2b09c5", "value": "\n
\n Location: (36.7397, 3.2864)
\n Soil Properties:
\n N: 60.0 | P: 55.0 | K: 44.0 | pH: 7.84 | EC: 0.9
\n Soil Type: FL
\n Climate Properties:
\n Bioclimatic Stage: SUB HUMID
\n Precipitation (mm): Monthly = 87.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 70.0
\n Wet Days: 10.2
\n Temperature: 9.8°C to 20.1°C | Mean = 14.9°C
\n Ground Frost: 0.8 | Relative Humidity: 72.2%
\n " } }, "4ac42b90c58f4c88bbd73c59c384fecc": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_1ad90fc35064416fbebedbc0687108b0", "placeholder": "​", "style": "IPY_MODEL_ebe604ec50954681b9351a89440dfc7d", "value": "\n
\n Location: (36.7416, 3.3226)
\n Soil Properties:
\n N: 71.0 | P: 46.0 | K: 40.0 | pH: 7.24 | EC: 1.0
\n Soil Type: FL
\n Climate Properties:
\n Bioclimatic Stage: SUB HUMID
\n Precipitation (mm): Monthly = 87.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 70.0
\n Wet Days: 10.2
\n Temperature: 9.8°C to 20.1°C | Mean = 14.9°C
\n Ground Frost: 0.8 | Relative Humidity: 72.2%
\n " } }, "7f50d3a4ca6d4c5cb3e9a535ab0958ad": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_0a26ed34a598407ba2ff1cad66472ba3", "placeholder": "​", "style": "IPY_MODEL_41a135efeb1540feb79d4b8df35674b6", "value": "\n
\n Location: (36.7476, 3.3226)
\n Soil Properties:
\n N: 69.0 | P: 37.0 | K: 42.0 | pH: 7.07 | EC: 0.9
\n Soil Type: FL
\n Climate Properties:
\n Bioclimatic Stage: SUB HUMID
\n Precipitation (mm): Monthly = 87.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 70.0
\n Wet Days: 10.2
\n Temperature: 9.8°C to 20.1°C | Mean = 14.9°C
\n Ground Frost: 0.8 | Relative Humidity: 72.2%
\n " } }, "90e1deb105984dfea9db93f0957591b0": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_72e9837eda8c4a55bb9ee4c69591132f", "placeholder": "​", "style": "IPY_MODEL_9844c07aa1364ebb95a16da4d54844e2", "value": "\n
\n Location: (36.7514, 3.3239)
\n Soil Properties:
\n N: 78.0 | P: 42.0 | K: 42.0 | pH: 7.63 | EC: 1.2
\n Soil Type: FL
\n Climate Properties:
\n Bioclimatic Stage: SUB HUMID
\n Precipitation (mm): Monthly = 87.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 70.0
\n Wet Days: 10.2
\n Temperature: 9.8°C to 20.1°C | Mean = 14.9°C
\n Ground Frost: 0.8 | Relative Humidity: 72.2%
\n " } }, "0698ca91f89749c78c892525c4250fb7": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_707fea8f81df4619af2410698ee18256", "placeholder": "​", "style": "IPY_MODEL_a42f9e111e524bf58d5e45139e653a9e", "value": "\n
\n Location: (36.7539, 3.3200)
\n Soil Properties:
\n N: 74.0 | P: 35.0 | K: 40.0 | pH: 6.98 | EC: 1.2
\n Soil Type: FL
\n Climate Properties:
\n Bioclimatic Stage: SUB HUMID
\n Precipitation (mm): Monthly = 87.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 70.0
\n Wet Days: 10.2
\n Temperature: 9.8°C to 20.1°C | Mean = 14.9°C
\n Ground Frost: 0.8 | Relative Humidity: 72.2%
\n " } }, "5007218135364b5b8cfe7625d032a947": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_744f86a2e49544978bf7353905918be0", "placeholder": "​", "style": "IPY_MODEL_78ffb7bf03d445e0ad0af99b1ad2226e", "value": "\n
\n Location: (36.7549, 3.3200)
\n Soil Properties:
\n N: 74.0 | P: 54.0 | K: 38.0 | pH: 7.12 | EC: 0.8799999999999999
\n Soil Type: FL
\n Climate Properties:
\n Bioclimatic Stage: SUB HUMID
\n Precipitation (mm): Monthly = 87.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 70.0
\n Wet Days: 10.2
\n Temperature: 9.8°C to 20.1°C | Mean = 14.9°C
\n Ground Frost: 0.8 | Relative Humidity: 72.2%
\n " } }, "ea6b8cd405b642ea87d4112956ba5cf9": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_a0dbd8006b9f4cb189ecb9a043280d88", "placeholder": "​", "style": "IPY_MODEL_699b23c3945d4dedacad831883c4972d", "value": "\n
\n Location: (36.7554, 3.3239)
\n Soil Properties:
\n N: 91.0 | P: 36.0 | K: 45.0 | pH: 5.95 | EC: 0.8799999999999999
\n Soil Type: FL
\n Climate Properties:
\n Bioclimatic Stage: SUB HUMID
\n Precipitation (mm): Monthly = 87.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 70.0
\n Wet Days: 10.2
\n Temperature: 9.8°C to 20.1°C | Mean = 14.9°C
\n Ground Frost: 0.8 | Relative Humidity: 72.2%
\n " } }, "7b2732d739c94dbfb0485d3adadc2321": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_f6c256e5ca1646aba67e6df2f6f94616", "placeholder": "​", "style": "IPY_MODEL_d633b02014664dd1ae16fc10849201db", "value": "\n
\n Location: (36.7741, 3.5517)
\n Soil Properties:
\n N: 68.0 | P: 58.0 | K: 38.0 | pH: 6.34 | EC: 1.0
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SUB HUMID
\n Precipitation (mm): Monthly = 91.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 68.4
\n Wet Days: 10.4
\n Temperature: 9.7°C to 19.9°C | Mean = 14.8°C
\n Ground Frost: 1.2 | Relative Humidity: 72.5%
\n " } }, "2b69f424a56744a785a61c9ac9506be8": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_a9e3dea1f28f4cca8b7c91441d98a222", "placeholder": "​", "style": "IPY_MODEL_f90b41288f5f4b1397165cd635e35a73", "value": "\n
\n Location: (36.7747, 3.5505)
\n Soil Properties:
\n N: 89.0 | P: 54.0 | K: 38.0 | pH: 6.69 | EC: 1.2
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SUB HUMID
\n Precipitation (mm): Monthly = 91.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 68.4
\n Wet Days: 10.4
\n Temperature: 9.7°C to 19.9°C | Mean = 14.8°C
\n Ground Frost: 1.2 | Relative Humidity: 72.5%
\n " } }, "dbce3c15a7f6432d8a92c96da272b890": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_9d6df120e411423786de1725c38b8239", "placeholder": "​", "style": "IPY_MODEL_15424af4b29a4445bba74210e7c9d88f", "value": "\n
\n Location: (36.7757, 3.5505)
\n Soil Properties:
\n N: 83.0 | P: 58.0 | K: 45.0 | pH: 5.88 | EC: 0.88
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SUB HUMID
\n Precipitation (mm): Monthly = 91.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 68.4
\n Wet Days: 10.4
\n Temperature: 9.7°C to 19.9°C | Mean = 14.8°C
\n Ground Frost: 1.2 | Relative Humidity: 72.5%
\n " } }, "c21403b9fceb4b6ca267bed9b5cc5438": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_8d2a549bf87d4033a0d3e7af4b2e4e18", "placeholder": "​", "style": "IPY_MODEL_9c6ad016450342f0b31caa5bf4060b80", "value": "\n
\n Location: (36.7761, 3.5517)
\n Soil Properties:
\n N: 93.0 | P: 58.0 | K: 38.0 | pH: 6.93 | EC: 1.0
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SUB HUMID
\n Precipitation (mm): Monthly = 91.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 68.4
\n Wet Days: 10.4
\n Temperature: 9.7°C to 19.9°C | Mean = 14.8°C
\n Ground Frost: 1.2 | Relative Humidity: 72.5%
\n " } }, "1acc611390364f8697ed8f78a047742b": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_aa52141710fb4f51bc6756feeac3efb9", "placeholder": "​", "style": "IPY_MODEL_07d784b440e04b37bd3723dbdfae16dd", "value": "\n
\n Location: (36.7772, 3.5467)
\n Soil Properties:
\n N: 99.0 | P: 55.0 | K: 35.0 | pH: 6.50 | EC: 0.7
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SUB HUMID
\n Precipitation (mm): Monthly = 91.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 68.4
\n Wet Days: 10.4
\n Temperature: 9.7°C to 19.9°C | Mean = 14.8°C
\n Ground Frost: 1.2 | Relative Humidity: 72.5%
\n " } }, "785f768b9ea947a0a24c782e4d0194d3": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_3ce7adf36d7b483cbedb50f7e4fca6e4", "placeholder": "​", "style": "IPY_MODEL_f9bcdd7af24a4dfba8c3797960aa270b", "value": "\n
\n Location: (36.7782, 3.5467)
\n Soil Properties:
\n N: 69.0 | P: 55.0 | K: 38.0 | pH: 5.70 | EC: 1.0
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SUB HUMID
\n Precipitation (mm): Monthly = 91.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 68.4
\n Wet Days: 10.4
\n Temperature: 9.7°C to 19.9°C | Mean = 14.8°C
\n Ground Frost: 1.2 | Relative Humidity: 72.5%
\n " } }, "0e44d81d604a4f7eabec3c7f714ee419": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_45451c6be99d45829977eb3beefb38df", "placeholder": "​", "style": "IPY_MODEL_ac1a115e179a4a2f8c5dd789cea2d36d", "value": "\n
\n Location: (36.7784, 3.5415)
\n Soil Properties:
\n N: 94.0 | P: 53.0 | K: 40.0 | pH: 5.72 | EC: 0.7
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SUB HUMID
\n Precipitation (mm): Monthly = 91.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 68.4
\n Wet Days: 10.4
\n Temperature: 9.7°C to 19.9°C | Mean = 14.8°C
\n Ground Frost: 1.2 | Relative Humidity: 72.5%
\n " } }, "c2ff9eb696b043da9c5a27a967ab20eb": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_2d1660b1be044c419d9099f34b4a5808", "placeholder": "​", "style": "IPY_MODEL_285252b95d8140fab284666eab3a52c9", "value": "\n
\n Location: (36.7794, 3.5415)
\n Soil Properties:
\n N: 72.0 | P: 40.0 | K: 38.0 | pH: 7.59 | EC: 0.9
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: SUB HUMID
\n Precipitation (mm): Monthly = 91.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 68.4
\n Wet Days: 10.4
\n Temperature: 9.7°C to 19.9°C | Mean = 14.8°C
\n Ground Frost: 1.2 | Relative Humidity: 72.5%
\n " } }, "391f7e5a73bf47518068149685cb644e": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_c10781159e98481bb674a4bd11a8cd94", "placeholder": "​", "style": "IPY_MODEL_f3318926956748bf97e0031192934c4c", "value": "\n
\n Location: (36.8131, 7.6941)
\n Soil Properties:
\n N: 64.0 | P: 45.0 | K: 43.0 | pH: 5.53 | EC: 1.2
\n Soil Type: VR
\n Climate Properties:
\n Bioclimatic Stage: SUB HUMID
\n Precipitation (mm): Monthly = 82.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 66.4
\n Wet Days: 11.3
\n Temperature: 10.2°C to 20.5°C | Mean = 15.3°C
\n Ground Frost: 0.9 | Relative Humidity: 74.9%
\n " } }, "1676ea05649b46a788a0316842b88851": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_79d3c2759b714deba7a2529d58854c61", "placeholder": "​", "style": "IPY_MODEL_50dbabb55df44b56bba67d8b9d1c4a0c", "value": "\n
\n Location: (36.8139, 7.6941)
\n Soil Properties:
\n N: 60.0 | P: 51.0 | K: 36.0 | pH: 6.03 | EC: 1.2
\n Soil Type: VR
\n Climate Properties:
\n Bioclimatic Stage: SUB HUMID
\n Precipitation (mm): Monthly = 82.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 66.4
\n Wet Days: 11.3
\n Temperature: 10.2°C to 20.5°C | Mean = 15.3°C
\n Ground Frost: 0.9 | Relative Humidity: 74.9%
\n " } }, "f5e40187c97f4ce88a84abc7d0a62676": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_6c0730448c6e4a13bcb7a52dc38aea6d", "placeholder": "​", "style": "IPY_MODEL_43f5e9597da440d784fbf6e0aed5bc90", "value": "\n
\n Location: (36.8214, 7.6983)
\n Soil Properties:
\n N: 62.0 | P: 42.0 | K: 36.0 | pH: 6.43 | EC: 1.2
\n Soil Type: VR
\n Climate Properties:
\n Bioclimatic Stage: SUB HUMID
\n Precipitation (mm): Monthly = 82.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 66.4
\n Wet Days: 11.3
\n Temperature: 10.2°C to 20.5°C | Mean = 15.3°C
\n Ground Frost: 0.9 | Relative Humidity: 74.9%
\n " } }, "f8af3def07474501986546d550a3cba9": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_077f4b5db7844f4db9d13220cc01da2d", "placeholder": "​", "style": "IPY_MODEL_05385e49a00c46e0934b2d275309b162", "value": "\n
\n Location: (36.8216, 7.6983)
\n Soil Properties:
\n N: 78.0 | P: 40.0 | K: 38.0 | pH: 7.55 | EC: 0.9
\n Soil Type: VR
\n Climate Properties:
\n Bioclimatic Stage: SUB HUMID
\n Precipitation (mm): Monthly = 82.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 66.4
\n Wet Days: 11.3
\n Temperature: 10.2°C to 20.5°C | Mean = 15.3°C
\n Ground Frost: 0.9 | Relative Humidity: 74.9%
\n " } }, "b27f54c74f3b4718bd53ca20248525f9": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_5b7d690ff0db48b78735806bf5d4acbb", "placeholder": "​", "style": "IPY_MODEL_f82025c3b89d43b1aa75165ab7b1268b", "value": "\n
\n Location: (36.8229, 7.6926)
\n Soil Properties:
\n N: 88.0 | P: 46.0 | K: 42.0 | pH: 6.60 | EC: 1.2
\n Soil Type: VR
\n Climate Properties:
\n Bioclimatic Stage: SUB HUMID
\n Precipitation (mm): Monthly = 82.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 66.4
\n Wet Days: 11.3
\n Temperature: 10.2°C to 20.5°C | Mean = 15.3°C
\n Ground Frost: 0.9 | Relative Humidity: 74.9%
\n " } }, "e45f8fd6381f467fb8404e3a4ed62982": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_c3b32ca922804c85acb60cc9bc9c76d1", "placeholder": "​", "style": "IPY_MODEL_8048ef8c5bff4868bd408143bd0b70a2", "value": "\n
\n Location: (36.8239, 7.6926)
\n Soil Properties:
\n N: 83.0 | P: 60.0 | K: 36.0 | pH: 6.90 | EC: 0.7
\n Soil Type: VR
\n Climate Properties:
\n Bioclimatic Stage: SUB HUMID
\n Precipitation (mm): Monthly = 82.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 66.4
\n Wet Days: 11.3
\n Temperature: 10.2°C to 20.5°C | Mean = 15.3°C
\n Ground Frost: 0.9 | Relative Humidity: 74.9%
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\n Location: (36.8248, 7.6900)
\n Soil Properties:
\n N: 82.0 | P: 40.0 | K: 40.0 | pH: 6.27 | EC: 0.88
\n Soil Type: VR
\n Climate Properties:
\n Bioclimatic Stage: SUB HUMID
\n Precipitation (mm): Monthly = 82.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 66.4
\n Wet Days: 11.3
\n Temperature: 10.2°C to 20.5°C | Mean = 15.3°C
\n Ground Frost: 0.9 | Relative Humidity: 74.9%
\n " } }, "aff18fb7637848079d6737e2586efe4a": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_dc2204fd80de4976b210bf4d5f417bd1", "placeholder": "​", "style": "IPY_MODEL_4d3ad23dfd774181a32639b736934f91", "value": "\n
\n Location: (36.8258, 7.6900)
\n Soil Properties:
\n N: 93.0 | P: 47.0 | K: 37.0 | pH: 6.50 | EC: 0.9
\n Soil Type: VR
\n Climate Properties:
\n Bioclimatic Stage: SUB HUMID
\n Precipitation (mm): Monthly = 82.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 66.4
\n Wet Days: 11.3
\n Temperature: 10.2°C to 20.5°C | Mean = 15.3°C
\n Ground Frost: 0.9 | Relative Humidity: 74.9%
\n " } }, "f6d05e8313e043e5a14578de647d8a83": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_1a8bf8be9ef8493eac7c6a25b338c6d1", "placeholder": "​", "style": "IPY_MODEL_0cd80923bb0e4ac1a21b350c65f862d3", "value": "\n
\n Location: (36.8327, 7.4660)
\n Soil Properties:
\n N: 79.0 | P: 43.0 | K: 39.0 | pH: 7.06 | EC: 0.7
\n Soil Type: VR
\n Climate Properties:
\n Bioclimatic Stage: SUB HUMID
\n Precipitation (mm): Monthly = 82.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 66.4
\n Wet Days: 11.3
\n Temperature: 10.2°C to 20.5°C | Mean = 15.3°C
\n Ground Frost: 0.9 | Relative Humidity: 74.9%
\n " } }, "b0d3378c8ce74e9fb2519bd853e4876a": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_3076ad8bf7d7443584aa266367f75fb7", "placeholder": "​", "style": "IPY_MODEL_762966a4cbc1476f9306c6323d89f4de", "value": "\n
\n Location: (36.8336, 7.4660)
\n Soil Properties:
\n N: 71.0 | P: 54.0 | K: 16.0 | pH: 5.75 | EC: 1.2
\n Soil Type: VR
\n Climate Properties:
\n Bioclimatic Stage: SUB HUMID
\n Precipitation (mm): Monthly = 82.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 66.4
\n Wet Days: 11.3
\n Temperature: 10.2°C to 20.5°C | Mean = 15.3°C
\n Ground Frost: 0.9 | Relative Humidity: 74.9%
\n " } }, "db9b8a3af36a41c4ad88a49d661cfeec": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_53426abc0b784a949a00baeca3975cb3", "placeholder": "​", "style": "IPY_MODEL_5fbe8a2f4d734060ab5f0d0df7774f82", "value": "\n
\n Location: (36.8337, 7.4660)
\n Soil Properties:
\n N: 61.0 | P: 44.0 | K: 17.0 | pH: 6.93 | EC: 0.9
\n Soil Type: VR
\n Climate Properties:
\n Bioclimatic Stage: SUB HUMID
\n Precipitation (mm): Monthly = 82.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 66.4
\n Wet Days: 11.3
\n Temperature: 10.2°C to 20.5°C | Mean = 15.3°C
\n Ground Frost: 0.9 | Relative Humidity: 74.9%
\n " } }, "737076aa6e674843a3e374e8fb9f7a77": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_d94906b3f9c44964a54e3cc185bb77dd", "placeholder": "​", "style": "IPY_MODEL_1ada7816dcfd4163b75afca736c51929", "value": "\n
\n Location: (36.8346, 7.4660)
\n Soil Properties:
\n N: 74.0 | P: 39.0 | K: 38.0 | pH: 7.78 | EC: 0.88
\n Soil Type: VR
\n Climate Properties:
\n Bioclimatic Stage: SUB HUMID
\n Precipitation (mm): Monthly = 82.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 66.4
\n Wet Days: 11.3
\n Temperature: 10.2°C to 20.5°C | Mean = 15.3°C
\n Ground Frost: 0.9 | Relative Humidity: 74.9%
\n " } }, "caeb14fca9834237892eba85f01f82fa": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_5b9b20293bcf4f2ba99955e47c833667", "placeholder": "​", "style": "IPY_MODEL_c2cfa7afa1aa456792b170dc7721f708", "value": "\n
\n Location: (36.8803, 7.0505)
\n Soil Properties:
\n N: 88.0 | P: 55.0 | K: 45.0 | pH: 7.73 | EC: 1.2
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: HUMID
\n Precipitation (mm): Monthly = 85.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 65.7
\n Wet Days: 10.9
\n Temperature: 10.5°C to 19.9°C | Mean = 15.200000000000001°C
\n Ground Frost: 1.0 | Relative Humidity: 74.5%
\n " } }, "8f15b0b5bacb4cf79c83e5713c8f9550": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_e70f60be660640bdbcccd8a019f972d6", "placeholder": "​", "style": "IPY_MODEL_896b5a72c1bf446f8e5dd5e201ab8ef6", "value": "\n
\n Location: (36.8810, 7.0568)
\n Soil Properties:
\n N: 60.0 | P: 36.0 | K: 43.0 | pH: 5.29 | EC: 1.0
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: HUMID
\n Precipitation (mm): Monthly = 85.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 65.7
\n Wet Days: 10.9
\n Temperature: 10.5°C to 19.9°C | Mean = 15.200000000000001°C
\n Ground Frost: 1.0 | Relative Humidity: 74.5%
\n " } }, "58cef70f4d294d9bb926938208ff340b": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_eb9bba0f35744181ab091818ff18fe13", "placeholder": "​", "style": "IPY_MODEL_15c50195f643456490d10f7803435bf1", "value": "\n
\n Location: (36.8813, 7.0505)
\n Soil Properties:
\n N: 80.0 | P: 43.0 | K: 16.0 | pH: 6.66 | EC: 0.8800000000000001
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: HUMID
\n Precipitation (mm): Monthly = 85.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 65.7
\n Wet Days: 10.9
\n Temperature: 10.5°C to 19.9°C | Mean = 15.200000000000001°C
\n Ground Frost: 1.0 | Relative Humidity: 74.5%
\n " } }, "c65a54dd081b488089b964f2f502070f": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_dac66076515544a4b1e634194c508e87", "placeholder": "​", "style": "IPY_MODEL_1fad70a040594e8982e4940b3c877519", "value": "\n
\n Location: (36.8819, 7.0568)
\n Soil Properties:
\n N: 73.0 | P: 58.0 | K: 21.0 | pH: 6.60 | EC: 0.9
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: HUMID
\n Precipitation (mm): Monthly = 85.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 65.7
\n Wet Days: 10.9
\n Temperature: 10.5°C to 19.9°C | Mean = 15.200000000000001°C
\n Ground Frost: 1.0 | Relative Humidity: 74.5%
\n " } }, "4bad19ee29aa485090470fd7fb65c61c": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_71ae084c53a446499b5cf0fe52087631", "placeholder": "​", "style": "IPY_MODEL_3bbbc9b5862d43bab3bd1b03981f6fcf", "value": "\n
\n Location: (36.8853, 7.0613)
\n Soil Properties:
\n N: 93.0 | P: 56.0 | K: 42.0 | pH: 7.38 | EC: 0.7000000000000001
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: HUMID
\n Precipitation (mm): Monthly = 85.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 65.7
\n Wet Days: 10.9
\n Temperature: 10.5°C to 19.9°C | Mean = 15.200000000000001°C
\n Ground Frost: 1.0 | Relative Humidity: 74.5%
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\n Location: (36.8856, 7.0571)
\n Soil Properties:
\n N: 76.0 | P: 60.0 | K: 39.0 | pH: 6.77 | EC: 0.8800000000000001
\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: HUMID
\n Precipitation (mm): Monthly = 85.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 65.7
\n Wet Days: 10.9
\n Temperature: 10.5°C to 19.9°C | Mean = 15.200000000000001°C
\n Ground Frost: 1.0 | Relative Humidity: 74.5%
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\n Location: (36.8859, 7.0613)
\n Soil Properties:
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\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: HUMID
\n Precipitation (mm): Monthly = 85.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 65.7
\n Wet Days: 10.9
\n Temperature: 10.5°C to 19.9°C | Mean = 15.200000000000001°C
\n Ground Frost: 1.0 | Relative Humidity: 74.5%
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\n Location: (36.8860, 7.0571)
\n Soil Properties:
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\n Soil Type: NT
\n Climate Properties:
\n Bioclimatic Stage: HUMID
\n Precipitation (mm): Monthly = 85.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 65.7
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\n Location: (36.8979, 7.6759)
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\n Climate Properties:
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\n Precipitation (mm): Monthly = 82.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 66.4
\n Wet Days: 11.3
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\n Soil Properties:
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\n Soil Type: VR
\n Climate Properties:
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\n Precipitation (mm): Monthly = 82.0 | Daily = 3.0
\n Precipitation Coefficient of Variation: 66.4
\n Wet Days: 11.3
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\n Location: (36.8989, 7.6759)
\n Soil Properties:
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\n Soil Type: VR
\n Climate Properties:
\n Bioclimatic Stage: SUB HUMID
\n Precipitation (mm): Monthly = 82.0 | Daily = 3.0
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\n Location: (36.8993, 7.6598)
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\n Soil Type: VR
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\n Soil Type: VR
\n Climate Properties:
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\n Precipitation (mm): Monthly = 82.0 | Daily = 3.0
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\n Soil Properties:
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\n Soil Type: VR
\n Climate Properties:
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Temporal Analysis

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Province: ADRAR

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Temporal Analysis

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Lat: 27.957, Lon: -0.343

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Province: ADRAR

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Temporal Analysis

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Province: ADRAR

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Temporal Analysis

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Lat: 27.968, Lon: -0.423

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Province: ADRAR

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\n " } }, "4b94df50a98e458ab276ceb81b646d07": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_38863c8521e3459d8266e48dad01b5fe", "placeholder": "​", "style": "IPY_MODEL_169e690d7bb24b6b87def0fcd7dbe38e", "value": "\n
\n

Temporal Analysis

\n

Lat: 27.974, Lon: -0.423

\n

Province: ADRAR

\n \n
\n " } }, "aba9f5f3a0034f7d95696f1e97c8982d": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_390a7a01d51a458883dec23bdb69c44a", "placeholder": "​", "style": "IPY_MODEL_f6e79936b77c49ee9172b1c411b2a133", "value": "\n
\n

Temporal Analysis

\n

Lat: 27.977, Lon: -0.309

\n

Province: ADRAR

\n \n
\n " } }, "56df8391ba744607b415610899771afc": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_c76c4380fc1c42edaa861c960b342f8f", "placeholder": "​", "style": "IPY_MODEL_f5e183dadf154e28bcdd4c585f59f149", "value": "\n
\n

Temporal Analysis

\n

Lat: 27.981, Lon: -0.389

\n

Province: ADRAR

\n \n
\n " } }, "dbe6c70a710b48e6a7509bdbfddd1040": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_d5202967c87240b7b41e30af8337f718", "placeholder": "​", "style": "IPY_MODEL_3c2098d66d23406aa920056e2137ca04", "value": "\n
\n

Temporal Analysis

\n

Lat: 27.991, Lon: -0.313

\n

Province: ADRAR

\n \n
\n " } }, "06486e6c36194ac4a38b0cf3c1ab9705": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_30f77f5951734f91970eff7d4f595aa2", "placeholder": "​", "style": "IPY_MODEL_615ee10ef8c74551b53598eaee6fb30b", "value": "\n
\n

Temporal Analysis

\n

Lat: 27.992, Lon: -0.399

\n

Province: ADRAR

\n \n
\n " } }, "e42cb859fc5a4c93af073b3750362d1b": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_3df46bc295c248b5b0c219edf564edeb", "placeholder": "​", "style": "IPY_MODEL_12d81cb2ba95437190da74ca1eab9bec", "value": "\n
\n

Temporal Analysis

\n

Lat: 31.605, Lon: -2.202

\n

Province: BECHAR

\n \n
\n " } }, "2da9194476184602b2637330b181cf55": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_171ac515773c4d89be84d4bb6e4f355a", "placeholder": "​", "style": "IPY_MODEL_cdf1e7b5c49c4797bcfa30334acdb916", "value": "\n
\n

Temporal Analysis

\n

Lat: 31.606, Lon: -2.201

\n

Province: BECHAR

\n \n
\n " } }, "73484478762b4835ba98aa4a911d1490": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_77ced52c17c14412ae82e143a3eb430a", "placeholder": "​", "style": "IPY_MODEL_b3dc6d1f59f24db488ef075583715d1e", "value": "\n
\n

Temporal Analysis

\n

Lat: 31.606, Lon: -2.201

\n

Province: BECHAR

\n \n
\n " } }, "e48b51c937cc442f89165bdea568d9a9": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_d5e729427635491bb6e4e833ed4f9171", "placeholder": "​", "style": "IPY_MODEL_f1fe4fbb69294aa3a65f97b1dc0a60a0", "value": "\n
\n

Temporal Analysis

\n

Lat: 31.607, Lon: -2.201

\n

Province: BECHAR

\n \n
\n " } }, "3bf67ce9b5e14d7ea4d3a5ec6856608b": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_d63098ec472c4034ac9c91ea8d318536", "placeholder": "​", "style": "IPY_MODEL_7710631b352e4526b47066d44b20ca43", "value": "\n
\n

Temporal Analysis

\n

Lat: 31.608, Lon: -2.201

\n

Province: BECHAR

\n \n
\n " } }, "a7db11a24e47418dbf4686351231849c": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_d3ab226062bb426b95ccfe97d0439076", "placeholder": "​", "style": "IPY_MODEL_01f17b1d5eac4fb3a67c81fa87481b41", "value": "\n
\n

Temporal Analysis

\n

Lat: 31.608, Lon: -2.205

\n

Province: BECHAR

\n \n
\n " } }, "d36b8f879a5a4dde80bf983fe928bcee": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_c57e80ce6caf42e5bda1e25552f2b5dc", "placeholder": "​", "style": "IPY_MODEL_4677babc453549e491a726bfb8bb74e9", "value": "\n
\n

Temporal Analysis

\n

Lat: 31.608, Lon: -2.204

\n

Province: BECHAR

\n \n
\n " } }, "a37f0e153a61479d93938771d855f98d": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_f61c63234ee94858a54ffac2fa3385c0", "placeholder": "​", "style": "IPY_MODEL_864e4431f19a4a0db1287b78da34c3f6", "value": "\n
\n

Temporal Analysis

\n

Lat: 31.609, Lon: -2.204

\n

Province: BECHAR

\n \n
\n " } }, "bce6de2d8bce4e0cb9ea46d675c11924": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_87cac6aa09d849f6b955fbf7925372dd", "placeholder": "​", "style": "IPY_MODEL_1a73ad3dd3a74969b98672be869db563", "value": "\n
\n

Temporal Analysis

\n

Lat: 33.228, Lon: 6.797

\n

Province: EL OUED

\n \n
\n " } }, "1905f14ca1df4459b5090624f939eb8d": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_bdf61944aa5b451eb93e09b44a61a9d0", "placeholder": "​", "style": "IPY_MODEL_77e87ca8aae9467d84bb71ed964326c9", "value": "\n
\n

Temporal Analysis

\n

Lat: 33.229, Lon: 6.781

\n

Province: EL OUED

\n \n
\n " } }, "ea8237bafba246a9bc96587fb8c298fb": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_7a3dcd2be01545418d05b02e674da6c2", "placeholder": "​", "style": "IPY_MODEL_997a69b9fdb04c948b2482889ab72213", "value": "\n
\n

Temporal Analysis

\n

Lat: 33.231, Lon: 6.749

\n

Province: EL OUED

\n \n
\n " } }, "682ce0d9bed9439cb94d4fe1c500b20c": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_b0ab411774554d939cff814772d1396a", "placeholder": "​", "style": "IPY_MODEL_8f2baed0fac246e7b9647206233bf75c", "value": "\n
\n

Temporal Analysis

\n

Lat: 33.231, Lon: 6.783

\n

Province: EL OUED

\n \n
\n " } }, "36168442e00a4e6fb856ed4afea336a8": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_ab93fe7a5aa44c909dcad33a701b9b04", "placeholder": "​", "style": "IPY_MODEL_5127ef0eb82645beb20d0f5c0fadb229", "value": "\n
\n

Temporal Analysis

\n

Lat: 33.257, Lon: 6.772

\n

Province: EL OUED

\n \n
\n " } }, "8ebdc74918ed42168a9a82700fccbffb": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_cc059961a2a6442c82b7fe0c89832bc9", "placeholder": "​", "style": "IPY_MODEL_a32d1d1316da4f06a9980b32cf2733b5", "value": "\n
\n

Temporal Analysis

\n

Lat: 33.272, Lon: 6.801

\n

Province: EL OUED

\n \n
\n " } }, "7f02189dc01149a39925c2530c1b868c": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_4d9b1a4571784d4eadb49810c9cbc743", "placeholder": "​", "style": "IPY_MODEL_ba41412ffc00437ebfa8b673a65bb250", "value": "\n
\n

Temporal Analysis

\n

Lat: 33.302, Lon: 6.853

\n

Province: EL OUED

\n \n
\n " } }, "9c4ee3b4068145e6aeb88db84a4ff35a": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_0517673c80f34ea8b549770a99010621", "placeholder": "​", "style": "IPY_MODEL_3a4642c889b64e33afee69bdf33577a4", "value": "\n
\n

Temporal Analysis

\n

Lat: 33.305, Lon: 6.858

\n

Province: EL OUED

\n \n
\n " } }, "43970e90542e400abb56e64ff9e95cc4": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_4b811252091f46b6b74e26c983b4d94e", "placeholder": "​", "style": "IPY_MODEL_fdee12cc9da24306adf5410552ddb4db", "value": "\n
\n

Temporal Analysis

\n

Lat: 33.307, Lon: 6.859

\n

Province: EL OUED

\n \n
\n " } }, "0a71c9d2fb9e4d02a83191a76b57ccfc": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_ebca70dae7c445a4a767fc015923a4c8", "placeholder": "​", "style": "IPY_MODEL_b74932ff627f40119bac1012c6a94ef5", "value": "\n
\n

Temporal Analysis

\n

Lat: 33.338, Lon: 6.888

\n

Province: EL OUED

\n \n
\n " } }, "5bb9b380f1a74f5b878f985682c9eee5": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_3b4ac5c1b64143edb071371508ad4dbb", "placeholder": "​", "style": "IPY_MODEL_1eee654183524958902b855533bd689f", "value": "\n
\n

Temporal Analysis

\n

Lat: 33.348, Lon: 6.877

\n

Province: EL OUED

\n \n
\n " } }, "042ea417623d4c6daf9ef5c9e794d86f": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_06437cdb22124b199e1390dbe747b397", "placeholder": "​", "style": "IPY_MODEL_f6fbb00a26184eb8bcc7915140dbf5ec", "value": "\n
\n

Temporal Analysis

\n

Lat: 33.363, Lon: 6.881

\n

Province: EL OUED

\n \n
\n " } }, "767ae4a9033a4659adcf7a9df13f8fba": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_f7ab8689893a43788840b4becba8bf51", "placeholder": "​", "style": "IPY_MODEL_04374c1a72ed440caa13d4fe9912eeb6", "value": "\n
\n

Temporal Analysis

\n

Lat: 35.123, Lon: -0.605

\n

Province: SIDI BEL ABBES

\n \n
\n " } }, "f78531429ea34710847ddbc4b81438e6": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_f457d18560c54dbb964f31f25ebed28a", "placeholder": "​", "style": "IPY_MODEL_3461a40fe9b14500a19536ae7bb5f008", "value": "\n
\n

Temporal Analysis

\n

Lat: 35.126, Lon: -0.643

\n

Province: SIDI BEL ABBES

\n \n
\n " } }, "670da4d270034d0995adc155f837ae88": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_1b8afa26ad5d46d69f26a57057240a92", "placeholder": "​", "style": "IPY_MODEL_e12962efca984ac2abed58065234ba12", "value": "\n
\n

Temporal Analysis

\n

Lat: 35.147, Lon: -0.611

\n

Province: SIDI BEL ABBES

\n \n
\n " } }, "a3f6894173214cebb62d766ed0d18300": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_4acdd7265ac549ec9c1291d80282d6c8", "placeholder": "​", "style": "IPY_MODEL_c295c08b821f4e31b3b9a41259cf9319", "value": "\n
\n

Temporal Analysis

\n

Lat: 35.150, Lon: -0.638

\n

Province: SIDI BEL ABBES

\n \n
\n " } }, "861d82061a5b4b239c7f5109266ffefa": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_c11729ec7ad545ac9d5344d298458155", "placeholder": "​", "style": "IPY_MODEL_481153907f654ba6ad113457a9019a3c", "value": "\n
\n

Temporal Analysis

\n

Lat: 35.164, Lon: -0.628

\n

Province: SIDI BEL ABBES

\n \n
\n " } }, "79def8cdeac14e64879127a33b2dffef": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_aef0777e55c94cd0b0b2e39176156b42", "placeholder": "​", "style": "IPY_MODEL_0283e49e5083412fa1884cda1ab5292d", "value": "\n
\n

Temporal Analysis

\n

Lat: 35.453, Lon: -0.547

\n

Province: ORAN

\n \n
\n " } }, "b922e90c1e2e413e81a6db88cdf5599f": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_9dbd0561941541b885e1622638ebe03a", "placeholder": "​", "style": "IPY_MODEL_0077b70516fa4a1f94da24e797839697", "value": "\n
\n

Temporal Analysis

\n

Lat: 35.455, Lon: -0.544

\n

Province: ORAN

\n \n
\n " } }, "ebf2396365ab4de2a7b3fb1ffbdd3e49": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_fed59d13af9642709482d4a7a6500d61", "placeholder": "​", "style": "IPY_MODEL_2f92ab097dcf405dbae8236d6250ef5a", "value": "\n
\n

Temporal Analysis

\n

Lat: 35.457, Lon: -0.537

\n

Province: ORAN

\n \n
\n " } }, "d6ec8051f69747919de649e12bfd9aeb": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_e9aee8bfa0294ac995431bee743dfa58", "placeholder": "​", "style": "IPY_MODEL_10ccadb165c34ffda5dbe2eae27f0ce6", "value": "\n
\n

Temporal Analysis

\n

Lat: 35.462, Lon: -0.527

\n

Province: ORAN

\n \n
\n " } }, "b24d2a5745a64145a36be9e9b61b2143": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_c3c8b1af18f64da48ae2393104e42254", "placeholder": "​", "style": "IPY_MODEL_7613f2beb3ec44159862992629d5741b", "value": "\n
\n

Temporal Analysis

\n

Lat: 35.544, Lon: -0.440

\n

Province: ORAN

\n \n
\n " } }, "2b743b34ddd4432aa9e233fa755bec32": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_8c6ba62eebc147a28427e943042f63fb", "placeholder": "​", "style": "IPY_MODEL_8429789d82ac4f19957f759460d40230", "value": "\n
\n

Temporal Analysis

\n

Lat: 35.545, Lon: -0.439

\n

Province: ORAN

\n \n
\n " } }, "91859bf0b1684ddaa796b6d879ca0647": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_e7532eff613a4c9c946cb7b766b57eb7", "placeholder": "​", "style": "IPY_MODEL_0023af71099f4eca9ca300dcc6929cfe", "value": "\n
\n

Temporal Analysis

\n

Lat: 35.546, Lon: -0.440

\n

Province: ORAN

\n \n
\n " } }, "3fd4b051b1de4b8c83d0170a3bfd8943": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_00639bed9bf942548e94d5a19b975b3b", "placeholder": "​", "style": "IPY_MODEL_be91b5404e1c4c918a8dd8daabeec56b", "value": "\n
\n

Temporal Analysis

\n

Lat: 35.618, Lon: 3.204

\n

Province: DJELFA

\n \n
\n " } }, "e0952b978d7a4ee8b2bb05649f43ee15": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_7f4ae6bad8184142b98731906155fe22", "placeholder": "​", "style": "IPY_MODEL_b9580a58e08b45238195edbcbcf55cd6", "value": "\n
\n

Temporal Analysis

\n

Lat: 35.619, Lon: 3.206

\n

Province: DJELFA

\n \n
\n " } }, "ce149d4687794db1bd57cfc5efcd4dc1": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_6dda2bfcdc414e5788d63191e803b186", "placeholder": "​", "style": "IPY_MODEL_b85ee88a5d7a4588aba6330d3b07903b", "value": "\n
\n

Temporal Analysis

\n

Lat: 35.620, Lon: 3.205

\n

Province: DJELFA

\n \n
\n " } }, "94b4597b82844188801b8bfe2440240b": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_5ef529fe5b9640e89a985cec6c0f5a2a", "placeholder": "​", "style": "IPY_MODEL_6e36ddb5db3b406e9bb7bbf1a1adee60", "value": "\n
\n

Temporal Analysis

\n

Lat: 35.634, Lon: 3.217

\n

Province: DJELFA

\n \n
\n " } }, "fd3a346d36534511bc43dcd5e1363920": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_34c95913842a43ce8db05b379794586b", "placeholder": "​", "style": "IPY_MODEL_e2128ebc01914c89b99188e6b307b477", "value": "\n
\n

Temporal Analysis

\n

Lat: 35.634, Lon: 3.215

\n

Province: DJELFA

\n \n
\n " } }, "6077288007de4fb8aacd7ff5c1e5737b": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_74178d3cbc1c4d6b9cf893354a93e5fd", "placeholder": "​", "style": "IPY_MODEL_9440926222164bdca46235a1e9b61a41", "value": "\n
\n

Temporal Analysis

\n

Lat: 35.635, Lon: 3.217

\n

Province: DJELFA

\n \n
\n " } }, "f5bf82341185493a95f4ddb50553cd14": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_31a354a9b109426c95a77041078395d7", "placeholder": "​", "style": "IPY_MODEL_07eb84a2f7fe4ac6a36c37c800f5d2be", "value": "\n
\n

Temporal Analysis

\n

Lat: 35.693, Lon: -0.509

\n

Province: ORAN

\n \n
\n " } }, "1d613a9920634980ae4e553923485338": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_5278d87b2c4f452eb2ac53a83644179d", "placeholder": "​", "style": "IPY_MODEL_6c85a55e1fa245dbb6d024fdf3c5c47b", "value": "\n
\n

Temporal Analysis

\n

Lat: 35.693, Lon: -0.509

\n

Province: ORAN

\n \n
\n " } }, "10f54ad7f3ae4723a2cc3ed771758dc7": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_df54f87ad4a949bba55de00c04686609", "placeholder": "​", "style": "IPY_MODEL_33589fef2b414c2dad33d0fd4d3dbb61", "value": "\n
\n

Temporal Analysis

\n

Lat: 35.694, Lon: -0.509

\n

Province: ORAN

\n \n
\n " } }, "53d21d1c3b9e41819c06a9709e17a4ea": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_2e75791289004498937b598711cc1454", "placeholder": "​", "style": "IPY_MODEL_5316b170b958423dbccae248fc86a6a8", "value": "\n
\n

Temporal Analysis

\n

Lat: 35.694, Lon: -0.510

\n

Province: ORAN

\n \n
\n " } }, "7ba6d32788234abcace94fd3a49f1dc8": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_f21c1823efdc4b90a5c30185d22eec03", "placeholder": "​", "style": "IPY_MODEL_ab8385e44e4e473ea607ad8886c5a8a1", "value": "\n
\n

Temporal Analysis

\n

Lat: 35.718, Lon: -0.556

\n

Province: ORAN

\n \n
\n " } }, "422637b180954a408569fd3f3232a5d4": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_24817fd141164344805537de8dac9ed3", "placeholder": "​", "style": "IPY_MODEL_f6f0d3d032f34f929f5041f3febbeded", "value": "\n
\n

Temporal Analysis

\n

Lat: 35.718, Lon: -0.555

\n

Province: ORAN

\n \n
\n " } }, "fda4d526dd9f45009d41ca6b8e531be5": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_12d963453d3e408885eae377a836266b", "placeholder": "​", "style": "IPY_MODEL_e4b9810f2baa41248fb951db1d7f540e", "value": "\n
\n

Temporal Analysis

\n

Lat: 35.720, Lon: -0.564

\n

Province: ORAN

\n \n
\n " } }, "4f09457d57f641d4874d791e28788580": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_c593788937ca4fa9bb59c09869f6c211", "placeholder": "​", "style": "IPY_MODEL_2450286953fc486bb48390d1837400dc", "value": "\n
\n

Temporal Analysis

\n

Lat: 35.720, Lon: -0.565

\n

Province: ORAN

\n \n
\n " } }, "bac8b0aab5b4483ea7c377d3585e96c8": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_7c11f57fd8244c159bfd77a344cb1f92", "placeholder": "​", "style": "IPY_MODEL_acd42f259fda4f098f740e053dd588af", "value": "\n
\n

Temporal Analysis

\n

Lat: 35.725, Lon: -0.565

\n

Province: ORAN

\n \n
\n " } }, "66750980e8ff4fd5887739e4de6336c9": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_ddba42894ef14ba59fa19eceb9b7baa1", "placeholder": "​", "style": "IPY_MODEL_92c782d247cd417b8e07bd53ebfd164c", "value": "\n
\n

Temporal Analysis

\n

Lat: 35.890, Lon: 0.063

\n

Province: MOSTAGANEM

\n \n
\n " } }, "6b16ec36788b423fa3484cc97803b249": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_ade615865b354a2ab80f76ffd872cd75", "placeholder": "​", "style": "IPY_MODEL_252b1d9659704eddb71401d7b572a984", "value": "\n
\n

Temporal Analysis

\n

Lat: 35.892, Lon: 0.065

\n

Province: MOSTAGANEM

\n \n
\n " } }, "063c0a948edb4b759a19fb73906e33de": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_e325919f9d904be3b2df7a15fdd86318", "placeholder": "​", "style": "IPY_MODEL_fb154a3d30be49c7b38426fb9f0de70d", "value": "\n
\n

Temporal Analysis

\n

Lat: 35.892, Lon: 0.064

\n

Province: MOSTAGANEM

\n \n
\n " } }, "851c35bfb0c741ab8f06672588b559b6": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_da03dad997f04c9db2654d971bb05757", "placeholder": "​", "style": "IPY_MODEL_f7dae056d2d9404c9a19a79d50ff9835", "value": "\n
\n

Temporal Analysis

\n

Lat: 35.893, Lon: 0.067

\n

Province: MOSTAGANEM

\n \n
\n " } }, "c33543fd89f94afdb45b9f16f80e4d89": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_1c6ada9049df408788b52b1286218bb4", "placeholder": "​", "style": "IPY_MODEL_fbab0c9fb1514fb5823a178229977fcf", "value": "\n
\n

Temporal Analysis

\n

Lat: 35.952, Lon: 0.125

\n

Province: MOSTAGANEM

\n \n
\n " } }, "f43b279d654d46aa9d966176825960f4": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_b4510272162547e2b7cd5d586457464b", "placeholder": "​", "style": "IPY_MODEL_015f1dc411664df09cfee6cb666f4d3b", "value": "\n
\n

Temporal Analysis

\n

Lat: 35.953, Lon: 0.127

\n

Province: MOSTAGANEM

\n \n
\n " } }, "0f001467a20948a2930b24179522ca33": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_c028b128a31241749f253388808c4b81", "placeholder": "​", "style": "IPY_MODEL_3e4f1de7e66047c7805db7071d209075", "value": "\n
\n

Temporal Analysis

\n

Lat: 35.954, Lon: 0.127

\n

Province: MOSTAGANEM

\n \n
\n " } }, "d3d2902807434144bd0b8568ef6c728f": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_ba6e5ea9b5f048f88da727ad16f74a2b", "placeholder": "​", "style": "IPY_MODEL_e87419f63df64f40b10cdfa4aa8e48a3", "value": "\n
\n

Temporal Analysis

\n

Lat: 35.955, Lon: 0.127

\n

Province: MOSTAGANEM

\n \n
\n " } }, "10fd9c433b0d4ebb85a1829401934b8b": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_bbd3b59f0033489abe049f324c97492c", "placeholder": "​", "style": "IPY_MODEL_40f3ddf88cad4669937ad337305ca1c7", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.311, Lon: 6.644

\n

Province: CONSTANTINE

\n \n
\n " } }, "e99646bf414b4e44b7dd70c795c0f11c": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_5f7115838ecd434f9b4118aa59c7d0e8", "placeholder": "​", "style": "IPY_MODEL_c184e5ad45324f73828f24948b963d3f", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.312, Lon: 6.644

\n

Province: CONSTANTINE

\n \n
\n " } }, "4ac47e116e5c4d9f8f4f53c645747f23": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_17b4fca8bb5e4814a518be006a74a485", "placeholder": "​", "style": "IPY_MODEL_3802ebdd56294027b61f60b3c83328e8", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.322, Lon: 6.634

\n

Province: CONSTANTINE

\n \n
\n " } }, "134d5457fb7a40f895062c40fee47800": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_0995e97424214005bcc2faaafc6bf768", "placeholder": "​", "style": "IPY_MODEL_8601289926b04335b30ba8109ad4d0b3", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.324, Lon: 6.634

\n

Province: CONSTANTINE

\n \n
\n " } }, "0317fa9122384a8db0385bea108bbce2": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_63c8220f9de44cd6a0f8486084a07419", "placeholder": "​", "style": "IPY_MODEL_12faaff7acaf447689a24952a7dc2839", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.347, Lon: 4.280

\n

Province: BOUIRA

\n \n
\n " } }, "298d2bd9b69449d98f4a0d73a453a300": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_3891dc53b8744553a7b0ad01686b341e", "placeholder": "​", "style": "IPY_MODEL_b6f1e0673ea0451e91df846e53a0acf7", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.348, Lon: 4.281

\n

Province: BOUIRA

\n \n
\n " } }, "faddea4ffd7e449bbe1cb9aa396ece59": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_e5b855f7e8ad446091a6a43717499902", "placeholder": "​", "style": "IPY_MODEL_b8a1ae1586b840dbbca4be49eacf1c85", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.349, Lon: 4.278

\n

Province: BOUIRA

\n \n
\n " } }, "0779b8676dfa4241a6e65e80eef9e401": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_4d39740b357047169067d413235fc825", "placeholder": "​", "style": "IPY_MODEL_b30debbb1f4a4bc9ba388e73c60fc435", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.349, Lon: 4.280

\n

Province: BOUIRA

\n \n
\n " } }, "154cdf91617f4f81937ed417a57eb298": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_e32e9a09e0d9488b87e7b02aad9c3a52", "placeholder": "​", "style": "IPY_MODEL_b8b54853fcf74a66bd89456c6c4ae0c6", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.350, Lon: 4.278

\n

Province: BOUIRA

\n \n
\n " } }, "44c3855c21a84741bbd5ea0dde107a9b": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_643026f873aa4023bb820929af5f6da5", "placeholder": "​", "style": "IPY_MODEL_236a30982d4d44c2a03dfb9c03d64cb5", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.350, Lon: 4.277

\n

Province: BOUIRA

\n \n
\n " } }, "196859a6f613471ba63947803a9ba9f7": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_71c38e62ca5042bbb1364839b85c4618", "placeholder": "​", "style": "IPY_MODEL_5347ca9536f1402fa2c95e9ff2b6c237", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.350, Lon: 4.280

\n

Province: BOUIRA

\n \n
\n " } }, "c1cc8bdc3d144ccfab9c7fa58544a102": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_382c33ea86844819865c0c8aabd404e6", "placeholder": "​", "style": "IPY_MODEL_5953b4a0b3b04252b96cccdfa7b2ccb7", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.351, Lon: 4.278

\n

Province: BOUIRA

\n \n
\n " } }, "87397bf43f9247d5907170d2e0f3214e": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_921a59509b094fa6baa45d0ff84572f7", "placeholder": "​", "style": "IPY_MODEL_2d62331d24694b93bb9715c72dc0a4cc", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.407, Lon: 7.465

\n

Province: GUELMA

\n \n
\n " } }, "ec7a5bf75f3b417e84d185c7981592f4": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_b58bc0b7b5e84ff482f26a329c021e5b", "placeholder": "​", "style": "IPY_MODEL_613cfca229bf42219d8ff88a6b912495", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.409, Lon: 7.465

\n

Province: GUELMA

\n \n
\n " } }, "9f14d24708c44d378c9a348010f0882c": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_10e728b80fac49879a49b6a2e87629d8", "placeholder": "​", "style": "IPY_MODEL_f50d8841d41049dc8ce7d5ec8f8ecec8", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.422, Lon: 7.483

\n

Province: GUELMA

\n \n
\n " } }, "f584c55508c94cf39091708c26208428": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_89fd6fba87d74496b700e781858fbdee", "placeholder": "​", "style": "IPY_MODEL_2d7bea09eecc49ef9a03b5be0c4af2a5", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.422, Lon: 7.483

\n

Province: GUELMA

\n \n
\n " } }, "5117268f579143c5969906c2fa153bbc": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_c659a0cf143a4653ae7cf999c9aee3f3", "placeholder": "​", "style": "IPY_MODEL_27401c46dbf0469b995d7dffc8f3a8cb", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.444, Lon: 7.250

\n

Province: GUELMA

\n \n
\n " } }, "0d6dcce7e15346e79d26977dfa1cab7b": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_8beb922472fe47c2866a192db770d79b", "placeholder": "​", "style": "IPY_MODEL_59cd25ecd62247699b9249353315466a", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.444, Lon: 7.258

\n

Province: GUELMA

\n \n
\n " } }, "61127fd5ed414c0cba74dad7aacc88b7": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_d236cd6afd624e3b984ed1dc63f10ab0", "placeholder": "​", "style": "IPY_MODEL_36b81b49f9574482a843156f23f784e6", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.445, Lon: 7.250

\n

Province: GUELMA

\n \n
\n " } }, "9a092c6a276445c7bc700f21d5453ed5": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_5c4be4be181244b3b794a967c6c61900", "placeholder": "​", "style": "IPY_MODEL_5ecb009fcf534d489f4960160f098a9b", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.446, Lon: 7.258

\n

Province: GUELMA

\n \n
\n " } }, "7adb6864b97247edaa98e8216c183029": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_15c13646b15f4ccf8d5ef0ae84d9f8c8", "placeholder": "​", "style": "IPY_MODEL_353cfa10fa064be6a3babfcd6bdbad28", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.448, Lon: 7.268

\n

Province: GUELMA

\n \n
\n " } }, "6d802b25c483452681a3c6a10438e7df": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_9cd6b1f0679b479a8b9a4c87bb2706e7", "placeholder": "​", "style": "IPY_MODEL_3371fcbb910348d8af30bb2a55bf6c25", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.450, Lon: 7.268

\n

Province: GUELMA

\n \n
\n " } }, "95640e483284427599869ea3550a56fa": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_021f3ba098cf41818b7553241d2c31b4", "placeholder": "​", "style": "IPY_MODEL_1ace861c7ce149f6a55c4c74d93f35ea", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.453, Lon: 7.385

\n

Province: GUELMA

\n \n
\n " } }, "058570826732484da7786bee7c7bdb76": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_e2cd2e057569413ca4b6db85f8713330", "placeholder": "​", "style": "IPY_MODEL_892d0049ffd94d6587fd9311af4b171e", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.454, Lon: 7.385

\n

Province: GUELMA

\n \n
\n " } }, "e42c1b0180a349f99ff9bdda8552a776": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_f31bddfb6268434ea051567189252ee5", "placeholder": "​", "style": "IPY_MODEL_45ab15198a3646c7a802c87a752fe452", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.466, Lon: 7.245

\n

Province: GUELMA

\n \n
\n " } }, "37a9fb402bb44369b9be8fda5423f99c": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_4f5e18900bd849718aadef2a6cc8a21e", "placeholder": "​", "style": "IPY_MODEL_965bef844b7741828db7b5e5bb0b8125", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.467, Lon: 7.245

\n

Province: GUELMA

\n \n
\n " } }, "e74b145524714af2affb5543eeef450f": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_e393e9be210e434e83d5b6d93913e8e4", "placeholder": "​", "style": "IPY_MODEL_89739316ff00403bac8b80d4180c9bc3", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.481, Lon: 7.505

\n

Province: GUELMA

\n \n
\n " } }, "e6453f7979414420a358bc4d5486084c": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_3d81ac2d27fa4935a99e12b67c418f1c", "placeholder": "​", "style": "IPY_MODEL_02017ea6fc29459a8c00d0cc51f5362f", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.482, Lon: 7.505

\n

Province: GUELMA

\n \n
\n " } }, "cd1da170e8804bc4afde222fa034399d": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_4664c3eff33b4798989b8b0f7dd97bec", "placeholder": "​", "style": "IPY_MODEL_b9a3ce45b3fd4a559c94e8594c0486f2", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.499, Lon: 7.348

\n

Province: GUELMA

\n \n
\n " } }, "844e819393ca40db80b62517b1109c38": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_1b2e83d3214e46afb1751b7d6e7c4db1", "placeholder": "​", "style": "IPY_MODEL_abca34ef8b28408c8e94e5ec145f8324", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.499, Lon: 7.348

\n

Province: GUELMA

\n \n
\n " } }, "3ea4cd122f6f4288b368185e059c8cd4": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_2fd8ad961dc2460290c6e40b4efca0c9", "placeholder": "​", "style": "IPY_MODEL_60e0d5eeffb74c2685bc96cd23c03602", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.572, Lon: 4.221

\n

Province: TIZI OUZOU

\n \n
\n " } }, "f18e3575d3144b419dcafb518826f6c6": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_2d602ddc0a5a4a609d3741c2d9e254cd", "placeholder": "​", "style": "IPY_MODEL_7377b7747606427c8b35364613ca497e", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.575, Lon: 4.221

\n

Province: TIZI OUZOU

\n \n
\n " } }, "b3240c56f6a24440bc84d4e663e43e42": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_59e3a3869eeb4504a1aecefa6e253c99", "placeholder": "​", "style": "IPY_MODEL_53e2335538ff4829a0fba07dd6c753ec", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.581, Lon: 4.224

\n

Province: TIZI OUZOU

\n \n
\n " } }, "b3286b0021e74875b2d2c5ce1783053e": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_1cebcfab140a4ac28eb4aeb5b7641810", "placeholder": "​", "style": "IPY_MODEL_fb408cebf1a242609ff28fcab9c9cd0d", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.583, Lon: 4.224

\n

Province: TIZI OUZOU

\n \n
\n " } }, "878ac8bc71ae46e099e1a8e75e56cf18": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_80b5f1d06ef24b41ae44e617899e0ca6", "placeholder": "​", "style": "IPY_MODEL_54bb9fa7959945149cac97982ba4662b", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.585, Lon: 4.207

\n

Province: TIZI OUZOU

\n \n
\n " } }, "a04393476cfd4276b050dbf146ef2b96": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_4107eefdf518465d8f2412cbdc03ae45", "placeholder": "​", "style": "IPY_MODEL_f7a250186fef40b2b2bdfd73035a6d2b", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.586, Lon: 4.207

\n

Province: TIZI OUZOU

\n \n
\n " } }, "69bc47aedb7d4ef3a9d51fc62dc6bde7": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_0eb03a1b716d4d3780d99dea541553f5", "placeholder": "​", "style": "IPY_MODEL_54f0b69ae451476da84dfb4536a03f10", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.592, Lon: 4.208

\n

Province: TIZI OUZOU

\n \n
\n " } }, "4265e9b6ec4c45739bf6d9f9536b68f1": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_b0de5f107bdd4efa870f6b0fdd4697d7", "placeholder": "​", "style": "IPY_MODEL_49882c867db247a6abe26609e75f6ebb", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.592, Lon: 4.208

\n

Province: TIZI OUZOU

\n \n
\n " } }, "04f8061a6d5641eeb1ecd0d6686f8bf9": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_46c4758c623f498182a8126f497a6e1c", "placeholder": "​", "style": "IPY_MODEL_3afefab99c0247469ae6684c497b90d6", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.631, Lon: 5.466

\n

Province: BEJAIA

\n \n
\n " } }, "eb25c9e048664f34bc44e355654a680e": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_9554598150d347919fb0feb23b3a86a3", "placeholder": "​", "style": "IPY_MODEL_076c85699f7f4a2fa6aa4d92e4680b58", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.632, Lon: 5.466

\n

Province: BEJAIA

\n \n
\n " } }, "c2be4633370443a382b2b0e65e3a4993": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_c20e0f49932444da81c63bd7695621bb", "placeholder": "​", "style": "IPY_MODEL_8127a51c514b4938ab2bd6277ed592ec", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.638, Lon: 5.483

\n

Province: BEJAIA

\n \n
\n " } }, "aa1ca489b9614c60ae92d74dfb29abd0": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_1354db1c4e674240b7c340f944dfb37b", "placeholder": "​", "style": "IPY_MODEL_c062c39940f94216904706416271e3f0", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.639, Lon: 5.483

\n

Province: BEJAIA

\n \n
\n " } }, "0990343de7dc4fc5ab485fb5a88bb0dc": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_737edd135c0d4c588ef83956e59f02dd", "placeholder": "​", "style": "IPY_MODEL_d5b5259161fc498bad5529014a0a50d7", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.643, Lon: 5.463

\n

Province: BEJAIA

\n \n
\n " } }, "370167d5938a4276afdbc36d3172ec0c": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_bddeb5b0d07042aaa85c3421798645ae", "placeholder": "​", "style": "IPY_MODEL_4b7038fd6ad840369e02562184965d76", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.644, Lon: 5.463

\n

Province: BEJAIA

\n \n
\n " } }, "87c9197d05bc4803a52c64b5ef72b396": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_5779a00cad9a408aa14daca75e4b24f3", "placeholder": "​", "style": "IPY_MODEL_5be2e642ed5b42e6aee17f4065849883", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.648, Lon: 4.925

\n

Province: BEJAIA

\n \n
\n " } }, "3006db17924c44ff856dee81f93a6525": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_ec9e220966c641e09f9966d7264bd5cf", "placeholder": "​", "style": "IPY_MODEL_356f85233969443785944d529f27eaad", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.649, Lon: 4.925

\n

Province: BEJAIA

\n \n
\n " } }, "c1cedba521b34915b54ce31909e5bd9d": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_bbc2b8be509d43d6aebb4eaf131104ec", "placeholder": "​", "style": "IPY_MODEL_3ea019f9e2a04de492c3b3238ae34562", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.653, Lon: 4.922

\n

Province: BEJAIA

\n \n
\n " } }, "19ce2ddf7e9940e9a92340969f12720d": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_90889d7ea4904912b8bb30f4d8e4225f", "placeholder": "​", "style": "IPY_MODEL_e6f763e703394e349fd96cc309850755", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.654, Lon: 4.922

\n

Province: BEJAIA

\n \n
\n " } }, "5bf3c29aeb464930858d485c9e8e1de8": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_a1554d2b34214acbaf99d09a81d5f551", "placeholder": "​", "style": "IPY_MODEL_b1d419a115014e12843330adcec22202", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.711, Lon: 6.455

\n

Province: SKIKDA

\n \n
\n " } }, "fe0d6d5ae9fe4eecbd53e0ea1bbc1120": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_ce3f4a9671c14eb4922fb4fca3878fd3", "placeholder": "​", "style": "IPY_MODEL_ce466f96123c426d8e57b8a52e467bcc", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.712, Lon: 6.455

\n

Province: SKIKDA

\n \n
\n " } }, "40a8bbd37f92466aa00f115b006767dc": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_304fbabc7cf84fc5b44f3d410763e33b", "placeholder": "​", "style": "IPY_MODEL_b3db5db3c37947f692921f9b0716185d", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.712, Lon: 6.446

\n

Province: SKIKDA

\n \n
\n " } }, "878e39904a7b4e918e0d394d4845e2ad": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_841562ae59cf4f449540f3de928887e0", "placeholder": "​", "style": "IPY_MODEL_de10d794dca34841a1d10dc10a72d20f", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.713, Lon: 6.446

\n

Province: SKIKDA

\n \n
\n " } }, "fb6bad1645ac4147a65dea0c19e793d5": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_83a035cb9bb846f39910304a6b66b5d0", "placeholder": "​", "style": "IPY_MODEL_87083b640ff54fc8bab0666293073052", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.715, Lon: 3.560

\n

Province: BOUMERDES

\n \n
\n " } }, "5dce88f784864ca7bac42c8da510b32d": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_dd868f921e1b48d187b279d64de7a872", "placeholder": "​", "style": "IPY_MODEL_4230b80caa6d43d6af9d109d26cc6725", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.715, Lon: 3.547

\n

Province: BOUMERDES

\n \n
\n " } }, "e41b1d4af59b477db70bb9582474f5a6": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_4c5e3e1df1564b6aaa7822a9866b2f70", "placeholder": "​", "style": "IPY_MODEL_d86bcd9ec32449c4b8a61a55fe054d38", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.716, Lon: 3.560

\n

Province: BOUMERDES

\n \n
\n " } }, "1a9cb5512aaf4a7ba6c063922d640735": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_c4b83c071f124f5b853027f31d61e76e", "placeholder": "​", "style": "IPY_MODEL_59b7a2132a7041d0bca6d68f2414911c", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.716, Lon: 3.546

\n

Province: BOUMERDES

\n \n
\n " } }, "72fdd2e6870d41a5bdf11a3577367aca": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_791ca42c5e144bdca2dcc0aa872c12fb", "placeholder": "​", "style": "IPY_MODEL_056e433db1ff412eaa4e153f20e4b7c4", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.717, Lon: 3.546

\n

Province: BOUMERDES

\n \n
\n " } }, "127067ab963d42cd9f18b0be1ebfa617": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_0de4efdef83a4dd4a6c1e6b782096366", "placeholder": "​", "style": "IPY_MODEL_c9034f8fce4c47d89c4404e0f30ad7df", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.718, Lon: 4.125

\n

Province: TIZI OUZOU

\n \n
\n " } }, "4340f2e45d1e4864a12b8e35a793f50b": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_fefa51a49256418e90ce118aa14c668a", "placeholder": "​", "style": "IPY_MODEL_f2220f738f1a4019a6c5b656893f30ef", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.719, Lon: 3.547

\n

Province: BOUMERDES

\n \n
\n " } }, "8df71569ff9f47c4ac37afa3f51b9042": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_fe6a9cb300d44e8997c841862562c1ff", "placeholder": "​", "style": "IPY_MODEL_36cba9550c784ad2bbad31b5f48cbd2e", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.719, Lon: 4.125

\n

Province: TIZI OUZOU

\n \n
\n " } }, "06d6fd9dbdf243b6b126cca33241294c": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_fc70a09f2bac40528f3c66203375fe16", "placeholder": "​", "style": "IPY_MODEL_5e1f25bed3f34693bf3fa2467ca6701b", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.733, Lon: 6.462

\n

Province: SKIKDA

\n \n
\n " } }, "1535b0d2ffe443518301a5af3eebb498": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_e7f0db4295fb46b99e2add0ab723c34b", "placeholder": "​", "style": "IPY_MODEL_4b20b74dacb54b4b90be98f12c74a470", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.735, Lon: 6.462

\n

Province: SKIKDA

\n \n
\n " } }, "da0e3241deaf4e27939bfb51b42b506c": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_3c12e56a07bd403cab3bf77ad8c1e3c3", "placeholder": "​", "style": "IPY_MODEL_ea2f87a47d1343e5a91f9cd0725c4851", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.736, Lon: 3.287

\n

Province: ALGER

\n \n
\n " } }, "48316ddc0ed7461e87cbd2d0d3250fa3": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_cf91446689f34807ba067ba782a97bf5", "placeholder": "​", "style": "IPY_MODEL_ca1fe17c3c48417299e0c8f388a03486", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.736, Lon: 3.285

\n

Province: ALGER

\n \n
\n " } }, "9add3e778caa4535a291b9fdadfb469d": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_fe775ca812104ca1915431e59f851359", "placeholder": "​", "style": "IPY_MODEL_d6b80664f4404d4e8c442a769e54ec8b", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.738, Lon: 3.286

\n

Province: ALGER

\n \n
\n " } }, "7df44437c986477598cee3e2afab2f9f": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_8ff17c5f78874b4a82ee185bbaad586e", "placeholder": "​", "style": "IPY_MODEL_9a970f4f8a974f659ad239d8cb1d1967", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.739, Lon: 3.287

\n

Province: ALGER

\n \n
\n " } }, "edefe7615fa9438f84e158a3c1d1456f": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_3760bbe48f5d47e0821a975925c10cef", "placeholder": "​", "style": "IPY_MODEL_ca28a28d3f80485199bac5749e4fb7ec", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.739, Lon: 3.285

\n

Province: ALGER

\n \n
\n " } }, "f8a3ce84d71d4831a9550e3ac6126144": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_6b57c0709c4341718558ba5e25db407a", "placeholder": "​", "style": "IPY_MODEL_431ee4331e0c4d6fb6fa1db65571923d", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.740, Lon: 3.286

\n

Province: ALGER

\n \n
\n " } }, "3dc10d2d59cd44409f9900b464ea5422": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_c69ea8e8d6f64b47ba48b79c09bd6959", "placeholder": "​", "style": "IPY_MODEL_d7abe57b427a4a1aa45779e5490b8b66", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.742, Lon: 3.323

\n

Province: ALGER

\n \n
\n " } }, "5f115b894c5c4d679efff725df5b9e47": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_5ce36da6a9c14db78647f52f60b80947", "placeholder": "​", "style": "IPY_MODEL_f486ded286bc4c8c9c321ebb20cb32a8", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.747, Lon: 7.883

\n

Province: EL TAREF

\n \n
\n " } }, "ba32c60a8465403eabf1d43b19a8cf35": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_c626dc76fe16485abfe614fbcd73e28e", "placeholder": "​", "style": "IPY_MODEL_b24339302997494c8804632b464c7674", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.748, Lon: 3.323

\n

Province: ALGER

\n \n
\n " } }, "989a4fc65377496487b6c42337c5aa7c": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_da62204809394b3384c2b41631cb3086", "placeholder": "​", "style": "IPY_MODEL_f2f3fea65ed64b0eb6f199423f21b42e", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.748, Lon: 7.883

\n

Province: EL TAREF

\n \n
\n " } }, "97da002ca8684127bbadd067ca14cac1": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_354fefcbc8c842a8aa1f14b99e65bb4a", "placeholder": "​", "style": "IPY_MODEL_638d555fd55b413ba1f9b37a6bce76af", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.750, Lon: 7.889

\n

Province: EL TAREF

\n \n
\n " } }, "9889087cc9e64351b5d30fbf84516d8b": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_0aa59a7d859f4f3690ff1f9da4579b9e", "placeholder": "​", "style": "IPY_MODEL_da6ab777a7514e679c80ad1b381279b0", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.751, Lon: 7.889

\n

Province: EL TAREF

\n \n
\n " } }, "fd8dd08263db4b7b90a49f55c6c16ea3": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_51522a9521f94c5a88c859b1400dd228", "placeholder": "​", "style": "IPY_MODEL_b686b892ac0f485da09a5756018125a4", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.751, Lon: 3.324

\n

Province: ALGER

\n \n
\n " } }, "0df178393773463cbb37a5f6af531771": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_2a07af0a2a104c65a3d1322975b5f7b8", "placeholder": "​", "style": "IPY_MODEL_1f33684846cb4fe68acd08f9de707ad6", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.754, Lon: 3.320

\n

Province: ALGER

\n \n
\n " } }, "b05931bc325d47e684d79a7b5928c4fa": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_a4326c46ece34e0b8c88456155afb054", "placeholder": "​", "style": "IPY_MODEL_ae74201d9c754603a9ed01b5c29dd2c0", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.755, Lon: 3.320

\n

Province: ALGER

\n \n
\n " } }, "dc8f68593bb24ae2b306e10569fa5a38": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_f5cc0fb6e83d4c5c896fd6496a18090a", "placeholder": "​", "style": "IPY_MODEL_29b02b4f171f44c39603292134828c3c", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.755, Lon: 3.324

\n

Province: ALGER

\n \n
\n " } }, "3a3c1501abda45458770c50f2aa1caaa": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_691e0f0c2c28449aac4870d27889bc46", "placeholder": "​", "style": "IPY_MODEL_2fd7c90dc3784709811d8850ee22fbf7", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.758, Lon: 7.884

\n

Province: EL TAREF

\n \n
\n " } }, "d8a4312e2b504a2784da42aa6b74005d": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_38bf870603074259842970a915afd558", "placeholder": "​", "style": "IPY_MODEL_dcb8a99d9bdc48adb1c5bf9af7c6941a", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.759, Lon: 7.884

\n

Province: EL TAREF

\n \n
\n " } }, "d600941e7a274359ad661c51f18a43c6": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_3e7aaac52ee64616a9068c5d1f2d70cd", "placeholder": "​", "style": "IPY_MODEL_4b647b16886c400090e19ad240c1d1f7", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.774, Lon: 3.552

\n

Province: BOUMERDES

\n \n
\n " } }, "c3353a91154849178a1b07237c7fd21e": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_0c7a309f82e9476eb1fd8b41dae19400", "placeholder": "​", "style": "IPY_MODEL_419030f41bff4cafbaacb0554336e5e6", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.775, Lon: 3.551

\n

Province: BOUMERDES

\n \n
\n " } }, "d7d5b87d46234e72956556fbcdedca53": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_d2d1146072e1441a9ec0eca2312d8e1f", "placeholder": "​", "style": "IPY_MODEL_7f8d48f480e24ad6833f632303731b50", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.776, Lon: 3.551

\n

Province: BOUMERDES

\n \n
\n " } }, "7ae18d266cc0404ea73c150bcaa68cda": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_cce7cfd323d342f796dc528eb86e5c18", "placeholder": "​", "style": "IPY_MODEL_998c342c83554684949c9cd3d99dd11f", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.776, Lon: 3.552

\n

Province: BOUMERDES

\n \n
\n " } }, "57fa2571a49b4b7b8ee56ea14b6225c1": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_31051fab264d41fc835c5093a2361e54", "placeholder": "​", "style": "IPY_MODEL_e6a19fc0cd1d4f5dbe759f32834de54b", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.777, Lon: 3.547

\n

Province: BOUMERDES

\n \n
\n " } }, "93a9f5041d964bd0b39d3164c0e46277": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_b7b0137436fc47aeb2e227b55a9b1591", "placeholder": "​", "style": "IPY_MODEL_4c5c0d7960924fcf9226299bba4ef4af", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.778, Lon: 3.547

\n

Province: BOUMERDES

\n \n
\n " } }, "c9dab9d417124cdaab9d94e26191c387": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_fb09a25320b44a87b5c8290794972336", "placeholder": "​", "style": "IPY_MODEL_21d84ca968004d4a80dd5e65b19bd33e", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.778, Lon: 3.542

\n

Province: BOUMERDES

\n \n
\n " } }, "201d01c48db145b09fc221d246164357": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_e55f520f980e4d1cb62acadb63766af4", "placeholder": "​", "style": "IPY_MODEL_b9313168030b4218b499e847c714f58e", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.779, Lon: 3.542

\n

Province: BOUMERDES

\n \n
\n " } }, "3e04f4f6e9e849dd80535f3b29d69760": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_3cfb63c6669344b38de7f162a8b8fd28", "placeholder": "​", "style": "IPY_MODEL_665eb4eb2d0b4bc58a14490fa80c2e24", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.813, Lon: 7.694

\n

Province: ANNABA

\n \n
\n " } }, "cbe8f3447ff24b278ce33f75486a74a9": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_8d227ab89e104af391196bf59cd56f64", "placeholder": "​", "style": "IPY_MODEL_7e6e1384bd61417ab10480ea4436b33d", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.814, Lon: 7.694

\n

Province: ANNABA

\n \n
\n " } }, "d6b381b4ce3c4eba93e3ffdedbececd2": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_11f2cccf3307430a925572c289fd2499", "placeholder": "​", "style": "IPY_MODEL_df315726652c4303b016c40666b909bd", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.821, Lon: 7.698

\n

Province: ANNABA

\n \n
\n " } }, "e6575ed8fa034d80bbf966e88b54b993": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_3d7aac4a016b492381870df77f931406", "placeholder": "​", "style": "IPY_MODEL_acc51faf262d49688dea12b0bfd37ccf", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.822, Lon: 7.698

\n

Province: ANNABA

\n \n
\n " } }, "215626d668844c52b8217090fc890279": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_f01301f672f24e89b42e0e42ea48a515", "placeholder": "​", "style": "IPY_MODEL_807f0c89389745c184f2507e7eb55d8a", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.823, Lon: 7.693

\n

Province: ANNABA

\n \n
\n " } }, "724712108d794c28afc7323dbccc1186": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_5e8acef3c4a444e49f7a16f52e89a109", "placeholder": "​", "style": "IPY_MODEL_0e1563ece24740699867c1bdcc37ac71", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.824, Lon: 7.693

\n

Province: ANNABA

\n \n
\n " } }, "8ae1b34d600b44c0812bb28b9c92c381": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_4d945811d6234cc4af9bd8d9f4fd001b", "placeholder": "​", "style": "IPY_MODEL_524a24b3005c41d9885ba0fa614ce676", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.825, Lon: 7.690

\n

Province: ANNABA

\n \n
\n " } }, "c9212b15725647adabed2af44fc9a130": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_5f1d65a25c674c6d87bb024a0ef68c56", "placeholder": "​", "style": "IPY_MODEL_2400835280644ba4ae76dc7944066710", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.826, Lon: 7.690

\n

Province: ANNABA

\n \n
\n " } }, "bbeabaf432d946c8b8c24ac3b94f0c81": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_d0e5eb5c45084c59b3c6509dc826a29f", "placeholder": "​", "style": "IPY_MODEL_962381a311014d6abc027be4cfec8ca9", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.833, Lon: 7.466

\n

Province: ANNABA

\n \n
\n " } }, "8991736fe2f8404fa3ce8bb914d48101": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_d5e065d2aebb449aada1e1f4cc5d275c", "placeholder": "​", "style": "IPY_MODEL_60a11e29809f419281fcf65128bebd3f", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.834, Lon: 7.466

\n

Province: ANNABA

\n \n
\n " } }, "51a45909fed642c18000cfa719e950a4": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_279b9c8594684ff2aa8bbcecf8c716dd", "placeholder": "​", "style": "IPY_MODEL_b1b36745e9ab42b2a3ff3af5bb2c1602", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.834, Lon: 7.466

\n

Province: ANNABA

\n \n
\n " } }, "c092fe4f55de4a419fa37594236db4f1": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_d560cb8284f94acba7a5246ab42c16bf", "placeholder": "​", "style": "IPY_MODEL_4bd95e9e38884c93815610f0121e96e5", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.835, Lon: 7.466

\n

Province: ANNABA

\n \n
\n " } }, "ee404f1402c1407cb849ccff041e1fa1": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_ccc52d1a6b4e4570918d4f9d2835c994", "placeholder": "​", "style": "IPY_MODEL_ab5b347112914dc8bdeedb557ff9109b", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.880, Lon: 7.051

\n

Province: SKIKDA

\n \n
\n " } }, "b742fe8c8cbc498cabe1bd7c4e4d38bb": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_01c1b9c02068497f9e5539732ff13e25", "placeholder": "​", "style": "IPY_MODEL_d838a5736e474a11b63892e96bde1092", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.881, Lon: 7.057

\n

Province: SKIKDA

\n \n
\n " } }, "3b63aced97d94aa489d51e593f12cca2": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_b4eb71fda8954238be21f7177e063fcd", "placeholder": "​", "style": "IPY_MODEL_f62ad6a27af44c0eaf3cc809254ba7d5", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.881, Lon: 7.051

\n

Province: SKIKDA

\n \n
\n " } }, "7974202ea8a54314b9f5cfc7a383659e": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_0e9d447eaba049ca989bfe0df0a29d2f", "placeholder": "​", "style": "IPY_MODEL_4de5d1f46e1f47b281d2ae8485cff016", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.882, Lon: 7.057

\n

Province: SKIKDA

\n \n
\n " } }, "7d63cb0a24194b1aa123616e7ce4867f": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_439cb94c11c04a36a3118439d10a9513", "placeholder": "​", "style": "IPY_MODEL_dcc5d5edeb34429d943a3eb1fd7018b1", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.885, Lon: 7.061

\n

Province: SKIKDA

\n \n
\n " } }, "1b436b00ea004144b3fa0990653212c6": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_6cc366d5945c463f8045b8f98eda7d2d", "placeholder": "​", "style": "IPY_MODEL_b12eb3e0d6014577957185b97fcad943", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.886, Lon: 7.057

\n

Province: SKIKDA

\n \n
\n " } }, "3d71cba3c8c44a908a175cdd6fd5a7f0": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_0c78aa3ce285437bbd692e0aef1af9bf", "placeholder": "​", "style": "IPY_MODEL_60d41b87355549ae8981959c110e7424", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.886, Lon: 7.061

\n

Province: SKIKDA

\n \n
\n " } }, "e865bffc9f50414d9b03b4ed3aef5bc6": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_ef6d49d183f0472ea2890316b29c82de", "placeholder": "​", "style": "IPY_MODEL_f39758b996c34bbeb771963356bc99f4", "value": "\n
\n

Temporal Analysis

\n

Lat: 36.886, Lon: 7.057

\n

Province: SKIKDA

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Temporal Analysis

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Temporal Analysis

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Temporal Analysis

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Temporal Analysis

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Temporal Analysis

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Temporal Analysis

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